20260103_002903/papers.csv

Rank,ID,Title,Authors,Year,Venue,Track,Status,Primary Area,Keywords,Citations,BM25 Score,Combined Score,DOI,URL,PDF,Source,TLDR,Abstract
1,RSvfY6dRVN,Learning and Reusing Abstract Latent Actions in a Hippocampal-Entorhinal-Inspired World Model,,2026,ICLR 2026,main,Active,applications to neuroscience & cognitive science,brain-inspired model;hippocampal-entorhinal coupling;inverse model;latent action;structural generalization;self-supervised learning,0,23.967,0.000,,https://openreview.net/forum?id=RSvfY6dRVN,,offline_iclr,,"Humans are capable of abstracting dynamic experiences into structured representations, facilitating both the inference of shared patterns by observing similar transition dynamics and the transfer of these structures across varied contexts. The hippocampal-entorhinal circuit, widely known for its rol"
2,8794144,Towards Learning Abstract Representations for Locomotion Planning in High-dimensional State Spaces,Tobias Klamt; Sven Behnke; Tobias Klamt; Sven Behnke,2019,ICRA 2019,main,Poster,,,0,23.017,0.000,,https://ieeexplore.ieee.org/document/8794144/,,offline_icra,,"Ground robots which are able to navigate a variety of terrains are needed in many domains. One of the key aspects is the capability to adapt to the ground structure, which can be realized through movable body parts coming along with additional degrees of freedom (DoF). However, planning respective l"
3,eBAMg7w96m,Understanding the Emergence of Seemingly Useless Features in Next-Token Predictors,,2026,ICLR 2026,main,Active,interpretability and explainable AI,next-token prediction;transformers;interpretability,0,22.593,0.000,,https://openreview.net/forum?id=eBAMg7w96m,,offline_iclr,,"Trained Transformers have been shown to compute abstract features that appear redundant for predicting the immediate next token. We identify which components of the gradient signal from the next-token prediction objective give rise to this phenomenon, and we propose a method to estimate the influenc"
4,czpx02orl7,Learning Abstract World Models for Value-preserving Planning with Options,Rafael Rodriguez-Sanchez; George Konidaris,2024,ICLR 2024,main,Reject,reinforcement learning,Model-based RL;Options;Temporal abstraction;State abstraction;Representation learning;reinforcement learning;MDPs,0,22.267,0.000,,https://openreview.net/forum?id=czpx02orl7,,offline_iclr,,"General-purpose agents require fine-grained controls and rich sensory inputs to perform a wide range of tasks. However, this complexity often leads to intractable decision-making. Traditionally, agents are provided with task-specific action and observation spaces to mitigate this challenge, but this"
5,a1zfcaNTkM,ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning,,2026,ICLR 2026,main,Active,"neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)",learning abstractions for planning;neuro-symbolic ai;concept learning,0,21.881,0.000,,https://openreview.net/forum?id=a1zfcaNTkM,,offline_iclr,,"Long‑horizon embodied planning is challenging because the world does not only change through an agent’s actions: exogenous processes (e.g., water heating, dominoes cascading) unfold concurrently with the agent's actions. We propose a framework for abstract world models that jointly learns (i) symbol"
6,QOfswj7hij,VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning,Yichao Liang; Nishanth Kumar; Hao Tang; Adrian Weller; Joshua B. Tenenbaum,2025,ICLR 2025,main,Spotlight,"neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)",learning abstractions for planning;neuro-symbolic ai;concept learning,0,21.805,0.000,,https://iclr.cc/virtual/2025/poster/29691,https://openreview.net/pdf?id=QOfswj7hij,offline_iclr,,"Broadly intelligent agents should form task-specific abstractions that selectively expose the essential elements of a task, while abstracting away the complexity of the raw sensorimotor space. In this work, we present Neuro-Symbolic Predicates, a first-order abstraction language that combines the st"
7,tpbtodnI1p,World Model Implanting for Test-time Adaptation of Embodied Agents,Minjong Yoo; Jinwoo Jang; Sihyung Yoon; Honguk Woo,2025,ICML 2025,main,Poster,reinforcement_learning->everything_else,Embodied AI;Model implanting;World models;Large language model,0,21.106,0.000,,https://icml.cc/virtual/2025/poster/43758,https://openreview.net/pdf?id=tpbtodnI1p,offline_icml,,"In embodied AI, a persistent challenge is enabling agents to robustly adapt to novel domains without requiring extensive data collection or retraining. To address this, we present a world model implanting framework (WorMI) that combines the reasoning capabilities of large language models (LLMs) with"
8,9340843,Graph-based Hierarchical Knowledge Representation for Robot Task Transfer from Virtual to Physical World,Zhenliang Zhang; Yixin Zhu; Song-Chun Zhu; Zhenliang Zhang; Yixin Zhu,2020,IROS 2020,main,Poster,,,0,20.791,0.000,,https://ieeexplore.ieee.org/document/9340843/,,offline_iros,,"We study the hierarchical knowledge transfer problem using a cloth-folding task, wherein the agent is first given a set of human demonstrations in the virtual world using an Oculus Headset, and later transferred and validated on a physical Baxter robot. We argue that such an intricate robot task tra"
9,GfPwZwZ9xZ,VLASim: World Modelling via VLM-Directed Abstraction and Simulation from a Single Image,,2026,ICLR 2026,main,Active,"applications to computer vision, audio, language, and other modalities",world models;video models;physical simulation;code generation,0,20.406,0.000,,https://openreview.net/forum?id=GfPwZwZ9xZ,,offline_iclr,,"Generative video models, a leading approach to world modeling, face fundamental limitations. They often violate physical and logical rules, lack interactivity, and operate as opaque black boxes ill-suited for building structured, queryable worlds. To overcome these challenges, we propose a new parad"
10,UIIi9hBNW8,"""You Are An Expert Linguistic Annotator"": Limits of LLMs as Analyzers of Abstract Meaning Representation",Allyson Ettinger; Jena D. Hwang; Valentina Pyatkin; Chandra Bhagavatula; Yejin Choi,2023,EMNLP 2023,main,Short Findings,,semantic structure;AMR;linguistic annotation;LLMs;few-shot;zero-shot,0,20.309,0.000,,https://openreview.net/forum?id=UIIi9hBNW8,,offline_emnlp,,"Large language models (LLMs) demonstrate an amazing proficiency and fluency in the $\textit{use}$ of language. Does that mean that they have also acquired insightful linguistic knowledge $\textit{about}$ the language, to an extent that they can serve as an ""expert linguistic annotator""? In this pape"
11,2022.findings-acl.244,AMR-DA: Data Augmentation by Abstract Meaning Representation,Ziyi Shou; Yuxin Jiang; Fangzhen Lin,2022,ACL 2022,main,Findings,,,0,20.145,0.000,,https://aclanthology.org/2022.findings-acl.244/,https://aclanthology.org/2022.findings-acl.244.pdf,offline_acl,,"Abstract Meaning Representation (AMR) is a semantic representation for NLP/NLU. In this paper, we propose to use it for data augmentation in NLP. Our proposed data augmentation technique, called AMR-DA, converts a sample sentence to an AMR graph, modifies the graph according to various data augmenta"
12,YeTYJz7th5,Learning Temporally AbstractWorld Models without Online Experimentation,Benjamin Freed; Siddarth Venkatraman; Guillaume Adrien Sartoretti; Jeff Schneider; Howie Choset,2023,ICML 2023,main,Poster,,,0,19.784,0.000,,https://icml.cc/virtual/2023/poster/23495,https://openreview.net/pdf?id=YeTYJz7th5,offline_icml,,"Agents that can build temporally abstract representations of their environment are better able to understand their world and make plans on extended time scales, with limited computational power and modeling capacity. However, existing methods for automatically learning temporally abstract world mode"
13,9136be0ae4,Predicting Object Dynamics in Scenes,David F. Fouhey; C. L. Zitnick,2014,CVPR 2014,main,Poster,,,0,19.541,0.000,,https://openaccess.thecvf.com/content_cvpr_2014/html/Fouhey_Predicting_Object_Dynamics_2014_CVPR_paper.html,https://openaccess.thecvf.com/content_cvpr_2014/papers/Fouhey_Predicting_Object_Dynamics_2014_CVPR_paper.pdf,offline_cvpr,,"Given a static scene, a human can trivially enumerate the myriad of things that can happen next and characterize the relative likelihood of each. In the process, we make use of enormous amounts of commonsense knowledge about how the world works. In this paper, we investigate learning this commonsens"
14,10610243,ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning,Qiao Gu; Ali Kuwajerwala; Sacha Morin; Krishna Murthy Jatavallabhula; Bipasha Sen,2024,ICRA 2024,main,Poster,,,0,19.478,0.000,,https://ieeexplore.ieee.org/document/10610243/,,offline_icra,,"For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and planning. Recent approaches have attempted to leverage features from large vision-language models to encode semantics in 3D"
15,4627,Improved Distributed Principal Component Analysis,Maria-Florina Balcan; Vandana Kanchanapally; Yingyu Liang; David Woodruff,2014,NIPS 2014,main,Poster,,,0,19.458,0.000,,https://nips.cc/virtual/2014/poster/4627,https://papers.nips.cc/paper_files/paper/2014/file/e968f1646c1c6c35422b64c0934772a4-Paper.pdf,offline_nips,,"We study the distributed computing setting in which there are multiple servers, each holding a set of points, who wish to compute functions on the union of their point sets. A key task in this setting is Principal Component Analysis (PCA), in which the servers would like to compute a low dimensional"
16,EHmjRIA4l2,Compositional World Models with Interpretable Abstractions,Vishwas Sathish; Rajesh P. N. Rao,2025,ICLR 2025,main,Withdraw,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",State-Action Abstractions;Predictive Coding;Hierarchical Planning;Compositional World Models;Contrastive Learning;Hypernetworks;Hierarchical Reinforcement Learning,0,19.440,0.000,,https://openreview.net/forum?id=EHmjRIA4l2,,offline_iclr,,"We present a modular and compositional approach to learning human-aligned world models via state-action hierarchies. Our approach is inspired by sensory-motor hierarchies in the mammalian brain. We model complex state transition dynamics as a sequence of simpler dynamics, which in turn can be modele"
17,9981405,DreamingV2: Reinforcement Learning with Discrete World Models without Reconstruction,Masashi Okada; Tadahiro Taniguchi; Masashi Okada; Tadahiro Taniguchi,2022,IROS 2022,main,Poster,,,0,19.249,0.000,,https://ieeexplore.ieee.org/document/9981405/,,offline_iros,,"The present paper proposes a novel reinforce-ment learning method with world models, DreamingV2, a collaborative extension of DreamerV2 and Dreaming. Dream- erV2 is a cutting-edge model-based reinforcement learning from pixels that uses discrete world models to represent latent states with categoric"
18,article-29354,Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning,Ruiqian Nai; Zixin Wen; Ji Li; Yuanzhi Li; Yang Gao,2024,AAAI 2024,main,Technical,machine learning iv,,0,19.222,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/29354,https://ojs.aaai.org/index.php/AAAI/article/view/29354/30555,offline_aaai,,"In representation learning, a disentangled representation is highly desirable as it encodes generative factors of data in a separable and compact pattern. Researchers have advocated leveraging disentangled representations to complete downstream tasks with encouraging empirical evidence. This paper f"
19,6697100,Applying rule-based context knowledge to build abstract semantic maps of indoor environments,Ziyuan Liu; Georg von Wichert; Ziyuan Liu; Georg von Wichert,2013,IROS 2013,main,Poster,,,0,19.039,0.000,,https://ieeexplore.ieee.org/document/6697100/,,offline_iros,,"In this paper, we propose a generalizable method that systematically combines data driven MCMC sampling and inference using rule-based context knowledge for data abstraction. In particular, we demonstrate the usefulness of our method in the scenario of building abstract semantic maps for indoor envi"
20,5f13f76606,Diffeomorphic Dimensionality Reduction,Christian Walder; Bernhard Schölkopf,2008,NIPS 2008,main,Poster,,,0,18.974,0.000,,https://papers.nips.cc/paper_files/paper/2008/hash/647bba344396e7c8170902bcf2e15551-Abstract.html,https://papers.nips.cc/paper_files/paper/2008/file/647bba344396e7c8170902bcf2e15551-Paper.pdf,offline_nips,,This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high and low dimensional spaces to be a diffeomorphism is a natural way of ensuring that pairwise distances are approximately p
21,vU0KbvQ91x,Learning to Abstract with Nonparametric Variational Information Bottleneck,Melika Behjati; Fabio James Fehr; James Henderson,2023,EMNLP 2023,main,Short Findings,,Representation Learning;Analysis of Neural Networks;Nonparametric Variational Information Bottleneck;Deep Learning,0,18.952,0.000,,https://openreview.net/forum?id=vU0KbvQ91x,,offline_emnlp,,"Learned representations at the level of characters, sub-words, words, and sentences, have each contributed to advances in understanding different NLP tasks and linguistic phenomena. However, learning textual embeddings is costly as they are tokenization specific and require different models to be tr"
22,article-25290,Universe Points Representation Learning for Partial Multi-Graph Matching,Zhakshylyk Nurlanov; Frank R. Schmidt; Florian Bernard,2023,AAAI 2023,main,Technical,computer vision ii,,0,18.862,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/25290,https://ojs.aaai.org/index.php/AAAI/article/view/25290/25062,offline_aaai,,"Many challenges from natural world can be formulated as a graph matching problem. Previous deep learning-based methods mainly consider a full two-graph matching setting. In this work, we study the more general partial matching problem with multi-graph cycle consistency guarantees. Building on a rece"
23,urueR03mkng,Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning,Christopher Michael Rytting; David Wingate,2021,NIPS 2021,main,Poster,,natural language processing;reasoning;transfer learning;generalization,0,18.733,0.000,,https://nips.cc/virtual/2021/poster/26937,https://openreview.net/pdf?id=urueR03mkng,offline_nips,We characterize the ability of connectionist pre-trained language models to generalize on symbolic reasoning tasks.,"Large natural language models (LMs) (such as GPT-3 or T5) demonstrate impressive abilities across a range of general NLP tasks. Here, we show that the knowledge embedded in such models provides a useful inductive bias, not just on traditional NLP tasks, but also in the nontraditional task of trainin"
24,2021.emnlp-main.81,Relational World Knowledge Representation in Contextual Language Models: A Review,Tara Safavi; Danai Koutra,2021,EMNLP 2021,main,Main,,,0,18.596,0.000,,https://aclanthology.org/2021.emnlp-main.81/,https://aclanthology.org/2021.emnlp-main.81.pdf,offline_emnlp,,"Relational knowledge bases (KBs) are commonly used to represent world knowledge in machines. However, while advantageous for their high degree of precision and interpretability, KBs are usually organized according to manually-defined schemas, which limit their expressiveness and require significant "
25,14015,Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs,Yanlin Wang; Hui Li,2021,AAAI 2021,main,Technical,Speech and Natural Language Processing III,,0,18.594,0.000,,https://aaai.org/papers/14015-code-completion-by-modeling-flattened-abstract-syntax-trees-as-graphs/,https://cdn.aaai.org/ojs/17650/17650-13-21144-1-2-20210518.pdf,offline_aaai,,"Code completion has become an essential component of integrated development environments. Contemporary code completion methods rely on the abstract syntax tree (AST) to generate syntactically correct code. However, they cannot fully capture the sequential and repetitive patterns of writing code and "
26,2023.findings-acl.662,Learning from a Friend: Improving Event Extraction via Self-Training with Feedback from Abstract Meaning Representation,Zhiyang Xu; Jay Yoon Lee; Lifu Huang,2023,ACL 2023,main,Findings,,,0,18.562,0.000,,https://aclanthology.org/2023.findings-acl.662/,https://aclanthology.org/2023.findings-acl.662.pdf,offline_acl,,"Data scarcity has been the main factor that hinders the progress of event extraction. To overcome this issue, we propose a Self-Training with Feedback (STF) framework that leverages the large-scale unlabeled data and acquires feedback for each new event prediction from the unlabeled data by comparin"
27,2025.acl-short.55,The Role of Abstract Representations and Observed Preferences in the Ordering of Binomials in Large Language Models,Zachary Nicholas Houghton; Kenji Sagae; Emily Morgan,2025,ACL 2025,main,Short,,,0,18.527,0.000,,https://aclanthology.org/2025.acl-short.55/,https://aclanthology.org/2025.acl-short.55.pdf,offline_acl,,To what extent do large language models learn abstract representations as opposed to more superficial aspects of their very large training corpora? We examine this question in the context of binomial ordering preferences involving two conjoined nouns in English. When choosing a binomial ordering (ra
28,2023.findings-acl.449,Leveraging Denoised Abstract Meaning Representation for Grammatical Error Correction,Hejing Cao; Dongyan Zhao,2023,ACL 2023,main,Findings,,,0,18.310,0.000,,https://aclanthology.org/2023.findings-acl.449/,https://aclanthology.org/2023.findings-acl.449.pdf,offline_acl,,"Grammatical Error Correction (GEC) is the task of correcting errorful sentences into grammatically correct, semantically consistent, and coherent sentences. Popular GEC models either use large-scale synthetic corpora or use a large number of human-designed rules. The former is costly to train, while"
29,6507e53d79,Generation of Internal Representation by α-Transformation,Ryotaro Kamimura,1993,NIPS 1993,main,Poster,,,0,18.205,0.000,,https://papers.nips.cc/paper_files/paper/1993/hash/98d6f58ab0dafbb86b083a001561bb34-Abstract.html,https://papers.nips.cc/paper_files/paper/1993/file/98d6f58ab0dafbb86b083a001561bb34-Paper.pdf,offline_nips,,Abstract Unavailable
30,2024.lrec-main.236,CALAMR: Component ALignment for Abstract Meaning Representation,Paul Landes; Barbara Di Eugenio,2024,COLING 2024,main,Main,,,0,18.197,0.000,,https://aclanthology.org/2024.lrec-main.236/,https://aclanthology.org/2024.lrec-main.236.pdf,offline_coling,,"We present Component ALignment for Abstract Meaning Representation (Calamr), a novel method for graph alignment that can support summarization and its evaluation. First, our method produces graphs that explain what is summarized through their alignments, which can be used to train graph based summar"
31,2024.findings-acl.962,PuzzleVQA: Diagnosing Multimodal Reasoning Challenges of Language Models with Abstract Visual Patterns,Yew Ken Chia; Vernon Toh; Deepanway Ghosal; Lidong Bing; Soujanya Poria,2024,ACL 2024,main,Findings,,,0,18.141,0.000,,https://aclanthology.org/2024.findings-acl.962/,https://aclanthology.org/2024.findings-acl.962.pdf,offline_acl,,"Large multimodal models extend the impressive capabilities of large language models by integrating multimodal understanding abilities. However, it is not clear how they can emulate the general intelligence and reasoning ability of humans. As recognizing patterns and abstracting concepts are key to g"
32,2025.coling-main.503,Making Large Language Models into World Models with Precondition and Effect Knowledge,Kaige Xie; Ian Yang; John Gunerli; Mark Riedl,2025,COLING 2025,main,Main,,,0,18.128,0.000,,https://aclanthology.org/2025.coling-main.503/,https://aclanthology.org/2025.coling-main.503.pdf,offline_coling,,"World models, which encapsulate the dynamics of how actions affect environments, are foundational to the functioning of intelligent agents. In this work, we explore the potential of Large Language Models (LLMs) to operate as world models. Although LLMs are not inherently designed to model real-world"
33,lzfzjYuWgY,Do LLMs Build World Representations? Probing Through the Lens of State Abstraction,Zichao Li; Yanshuai Cao; Jackie CK Cheung,2024,NIPS 2024,main,Poster,natural_language_processing,Large Language Models;World Models;World Representation;Probing;Reinforcement Learning;State Abstraction,0,18.103,0.000,,https://neurips.cc/virtual/2024/poster/93786,https://openreview.net/pdf?id=lzfzjYuWgY,offline_nips,,"How do large language models (LLMs) encode the state of the world, including the status of entities and their relations, as described by a text? While existing work directly probes for a complete state of the world, our research explores whether and how LLMs abstract this world state in their intern"
34,2024.findings-acl.353,Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning,Qiming Bao; Alex Yuxuan Peng; Zhenyun Deng; Wanjun Zhong; Gaël Gendron,2024,ACL 2024,main,Findings,,,0,18.060,0.000,,https://aclanthology.org/2024.findings-acl.353/,https://aclanthology.org/2024.findings-acl.353.pdf,offline_acl,,"Combining large language models with logical reasoning enhances their capacity to address problems in a robust and reliable manner. Nevertheless, the intricate nature of logical reasoning poses challenges when gathering reliable data from the web to build comprehensive training datasets, subsequentl"
35,2024.lrec-main.26,A Corpus of German Abstract Meaning Representation (DeAMR),Christoph Otto; Jonas Groschwitz; Alexander Koller; Xiulin Yang; Lucia Donatelli,2024,COLING 2024,main,Main,,,0,18.057,0.000,,https://aclanthology.org/2024.lrec-main.26/,https://aclanthology.org/2024.lrec-main.26.pdf,offline_coling,,"We present the first comprehensive set of guidelines for German Abstract Meaning Representation (Deutsche AMR, DeAMR) along with an annotated corpus of 400 DeAMR. Taking English AMR (EnAMR) as our starting point, we propose significant adaptations to faithfully represent the structure and semantics "
36,eeeed0d0be,Strategy Grafting in Extensive Games,Kevin Waugh; Nolan Bard; Michael Bowling,2009,NIPS 2009,main,Poster,,,0,18.010,0.000,,https://papers.nips.cc/paper_files/paper/2009/hash/e0ec453e28e061cc58ac43f91dc2f3f0-Abstract.html,https://papers.nips.cc/paper_files/paper/2009/file/e0ec453e28e061cc58ac43f91dc2f3f0-Paper.pdf,offline_nips,,"Extensive games are often used to model the interactions of multiple agents within an environment.  Much recent work has focused on increasing the size of an extensive game that can be feasibly solved.  Despite these improvements, many interesting games are still too large for such techniques.  A co"
37,2023.findings-acl.260,AMR-TST: Abstract Meaning Representation-based Text Style Transfer,Kaize Shi; Xueyao Sun; Li He; Dingxian Wang; Qing Li,2023,ACL 2023,main,Findings,,,0,17.932,0.000,,https://aclanthology.org/2023.findings-acl.260/,https://aclanthology.org/2023.findings-acl.260.pdf,offline_acl,,"Abstract Meaning Representation (AMR) is a semantic representation that can enhance natural language generation (NLG) by providing a logical semantic input. In this paper, we propose the AMR-TST, an AMR-based text style transfer (TST) technique. The AMR-TST converts the source text to an AMR graph a"
38,gnXTDQyxlU,PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation,Kaidong Zhang; Pengzhen Ren; Bingqian Lin; Junfan Lin; Shikui Ma,2024,NIPS 2024,main,Poster,robotics,Robot manipulation; World model,0,17.896,0.000,,https://neurips.cc/virtual/2024/poster/94118,https://openreview.net/pdf?id=gnXTDQyxlU,offline_nips,,"Language-guided robotic manipulation is a challenging task that requires an embodied agent to follow abstract user instructions to accomplish various complex manipulation tasks. Previous work generally maps instructions and visual perceptions directly to low-level executable actions, neglecting the "
39,KC58bVmxyN,A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks,Haruo Hosoya,2024,ICLR 2024,main,Poster,applications to neuroscience & cognitive science,Brain-inspired model; hippocampus; entorhinal cortex; memory; relational representation,0,17.888,0.000,,https://iclr.cc/virtual/2024/poster/18912,https://openreview.net/pdf?id=KC58bVmxyN,offline_iclr,,"Motivated by a recent neuroscientific hypothesis, some theoretical studies have accounted for neural cognitive maps in the rodent hippocampal formation as a representation of the general relational structure across task environments.  However, despite their remarkable results, it is unclear whether "
40,VgtpRXhxli,Efficient Fairness-Performance Pareto Front Computation,Mark Kozdoba; Binyamin Perets; Shie Mannor,2025,ICLR 2025,main,Reject,"alignment, fairness, safety, privacy, and societal considerations",Fairness;fair Representations;Fairness-Performance Pareto Front;Pareto Front;convex concave optimization,0,17.879,0.000,,https://openreview.net/forum?id=VgtpRXhxli,,offline_iclr,,"There is a well known intrinsic trade-off between the fairness of a representation and the performance of classifiers derived from the representation. 
Due to the complexity of optimisation algorithms in most modern representation learning approaches, for a given method it may be non-trivial to deci"
41,Rm5Qi57C5I,Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling,Kolby Nottingham; Prithviraj Ammanabrolu; Alane Suhr; Yejin Choi; Hannaneh Hajishirzi,2023,ICML 2023,main,Poster,,,0,17.803,0.000,,https://icml.cc/virtual/2023/poster/24286,https://openreview.net/pdf?id=Rm5Qi57C5I,offline_icml,,"Reinforcement learning (RL) agents typically learn tabula rasa, without prior knowledge of the world. However, if initialized with knowledge of high-level subgoals and transitions between subgoals, RL agents could utilize this Abstract World Model (AWM) for planning and exploration. We propose using"
42,2024.emnlp-main.1203,"Unveiling the mystery of visual attributes of concrete and abstract concepts: Variability, nearest neighbors, and challenging categories",Tarun Tater; Sabine Schulte Im Walde; Diego Frassinelli,2024,EMNLP 2024,main,Main,,,0,17.782,0.000,,https://aclanthology.org/2024.emnlp-main.1203/,https://aclanthology.org/2024.emnlp-main.1203.pdf,offline_emnlp,,"The visual representation of a concept varies significantly depending on its meaning and the context where it occurs; this poses multiple challenges both for vision and multimodal models. Our study focuses on concreteness, a well-researched lexical-semantic variable, using it as a case study to exam"
43,23216,Intrinsic Physical Concepts Discovery With Object-Centric Predictive Models,Qu Tang; Xiangyu Zhu; Zhen Lei; Zhaoxiang Zhang,2023,CVPR 2023,main,Poster,,,0,17.765,0.000,,https://cvpr.thecvf.com/virtual/2023/poster/23216,https://openaccess.thecvf.com/content/CVPR2023/papers/Tang_Intrinsic_Physical_Concepts_Discovery_With_Object-Centric_Predictive_Models_CVPR_2023_paper.pdf,offline_cvpr,,The ability to discover abstract physical concepts and understand how they work in the world through observing lies at the core of human intelligence. The acquisition of this ability is based on compositionally perceiving the environment in terms of objects and relations in an unsupervised manner. R
44,3sWghzJvGd,Towards Unraveling and Improving Generalization in World Models,Qiaoyi Fang; Weiyu Du; Hang Wang; Junshan Zhang,2024,NIPS 2024,main,Reject,reinforcement_learning,world models;reinforcement learning;generalization,0,17.760,0.000,,https://openreview.net/forum?id=3sWghzJvGd,,offline_nips,,"World model has recently emerged as a promising approach to reinforcement learning (RL), as evidenced by its great successes that world model based agents exhibit state-of-the-art performance on a wide range visual control tasks. In this study, we aim to first obtain a clear understanding of the gen"
45,2023.findings-acl.131,Exploiting Abstract Meaning Representation for Open-Domain Question Answering,Cunxiang Wang; Zhikun Xu; Qipeng Guo; Xiangkun Hu; Xuefeng Bai,2023,ACL 2023,main,Findings,,,0,17.723,0.000,,https://aclanthology.org/2023.findings-acl.131/,https://aclanthology.org/2023.findings-acl.131.pdf,offline_acl,,"The Open-Domain Question Answering (ODQA) task involves retrieving and subsequently generating answers from fine-grained relevant passages within a database. Current systems leverage Pretrained Language Models (PLMs) to model the relationship between questions and passages. However, the diversity in"
46,H1gax6VtDB,Contrastive Learning of Structured World Models,Thomas Kipf; Elise van der Pol; Max Welling,2020,ICLR 2020,main,Talk,,state representation learning;graph neural networks;model-based reinforcement learning;relational learning;object discovery,0,17.697,0.000,,https://openreview.net/forum?id=H1gax6VtDB,,offline_iclr,Contrastively-trained Structured World Models (C-SWMs) learn object-oriented state representations and a relational model of an environment from raw pixel input.,"A structured understanding of our world in terms of objects, relations, and hierarchies is an important component of human cognition. Learning such a structured world model from raw sensory data remains a challenge. As a step towards this goal, we introduce Contrastively-trained Structured World Mod"
47,Pnr8XNWcY0,Roadmap towards Superhuman Speech Understanding using Large Language Models,FanBu; Yuhao Zhang; Xidong Wang; Benyou Wang; Qun Liu,2025,ICLR 2025,main,Withdraw,"applications to computer vision, audio, language, and other modalities",Large langauge models; speech language models;,0,17.685,0.000,,https://openreview.net/forum?id=Pnr8XNWcY0,,offline_iclr,,"The success of large language models (LLMs) has prompted efforts to integrate speech and audio data, aiming to create general foundation models capable of processing both textual and non-textual inputs. Recent advances, such as GPT-4o, highlight the potential for end-to-end speech LLMs, which preser"
48,k7nYm2yU5i,Towards Understanding Robustness and Generalization in World Models,Qiaoyi Fang; Weiyu Du; Hang Wang; Junshan Zhang,2025,ICLR 2025,main,Withdraw,reinforcement learning,World models;robustness;generalization;model-based reinforcement learning,0,17.683,0.000,,https://openreview.net/forum?id=k7nYm2yU5i,,offline_iclr,,"World model has recently emerged as a promising approach to reinforcement learning (RL), as evidenced by the recent successes that world model based agents achieve state-of-the-art performance on a wide range of visual control tasks. This work aims to obtain a deep understanding of the robustness an"
49,AvSIqjCWVId,Abstract Visual Reasoning by Self-supervised Contrastive Learning,Weiwen Lu; Aihua Yin; Sidong Wang; Hongzhi You; Ru-Yuan Zhang,2023,ICLR 2023,main,Reject,,,0,17.653,0.000,,https://openreview.net/forum?id=AvSIqjCWVId,,offline_iclr,Demonstration of an unsupervised model to solve analogy reasoning in Raven’s Progressive Matrices task and its variant.  ,"Neuro-symbolic models of artificial intelligence (AI) have been recently developed to perform tasks involving abstract visual reasoning that is a hallmark of human intelligence but remains challenging for deep neural network methods. However, most of the current neuro-symbolic models also rely on su"
50,article-28122,Text-to-Image Generation for Abstract Concepts,Jiayi Liao; Xu Chen; Qiang Fu; Lun Du; Xiangnan He,2024,AAAI 2024,main,Technical,computer vision iii,,0,17.652,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/28122,https://ojs.aaai.org/index.php/AAAI/article/view/28122/28248,offline_aaai,,"Recent years have witnessed the substantial progress of large-scale models across various domains, such as natural language processing and computer vision, facilitating the expression of concrete concepts. Unlike concrete concepts that are usually directly associated with physical objects, expressin"
51,cxKLRM3KhC,Residual Connections Harm Generative Representation Learning,Xiao Zhang; Ruoxi Jiang; Will Gao; Rebecca Willett; Michael Maire,2025,ICLR 2025,main,Reject,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",Decayed Residual Connections;Representation Learning,0,17.556,0.000,,https://openreview.net/forum?id=cxKLRM3KhC,,offline_iclr,,"We show that introducing a weighting factor to reduce the influence of identity shortcuts in residual networks significantly enhances semantic feature learning in generative representation learning frameworks, such as masked autoencoders (MAEs) and diffusion models.  Our modification improves linear"
52,2022.coling-1.49,Semantic-based Pre-training for Dialogue Understanding,Xuefeng Bai; Linfeng Song; Yue Zhang,2022,COLING 2022,main,Main,,,0,17.513,0.000,,https://aclanthology.org/2022.coling-1.49/,https://aclanthology.org/2022.coling-1.49.pdf,offline_coling,,"Pre-trained language models have made great progress on dialogue tasks. However, these models are typically trained on surface dialogue text, thus are proven to be weak in understanding the main semantic meaning of a dialogue context. We investigate Abstract Meaning Representation (AMR) as explicit "
53,8BJl6LQgW5,Visual Representation Learning for World Models by Predicting Fine-Grained Motion,Zhao-Han Peng; Shaohui Li; Zhi Li; Yu LIU; You He,2025,ICLR 2025,main,Withdraw,reinforcement learning,world models;model-based reinforcement learning;visual representation learning,0,17.443,0.000,,https://openreview.net/forum?id=8BJl6LQgW5,,offline_iclr,,"Originating from model-based reinforcement learning (MBRL) methods, algorithms based on world models have been widely applied to boost sample efficiency in visual environments. However, existing world models often struggle with irrelevant background information and omit moving tiny objects that can "
54,nb3VjILNVs,Low Compute Unlearning via Sparse Representations,Vedant Shah; Frederik Träuble; Ashish Malik; Hugo Larochelle; Michael Curtis Mozer,2025,ICLR 2025,main,Reject,"alignment, fairness, safety, privacy, and societal considerations",Sparse Representations;Discrete Bottlenecks;Model Editing;Unlearning,0,17.430,0.000,,https://openreview.net/forum?id=nb3VjILNVs,,offline_iclr,,"Machine \emph{unlearning}, which involves erasing knowledge about a \emph{forget set} from a trained model, can prove to be 
costly and infeasible using existing techniques. We propose a  low compute unlearning technique based on a discrete representational bottleneck. We show that the proposed tech"
55,29182,ReCoRe: Regularized Contrastive Representation Learning of World Model,Rudra P.K. Poudel; Harit Pandya; Stephan Liwicki; Roberto Cipolla,2024,CVPR 2024,main,Poster,,,0,17.414,0.000,,https://cvpr.thecvf.com/virtual/2024/poster/29182,https://openaccess.thecvf.com/content/CVPR2024/papers/Poudel_ReCoRe_Regularized_Contrastive_Representation_Learning_of_World_Model_CVPR_2024_paper.pdf,offline_cvpr,,While recent model-free Reinforcement Learning (RL) methods have demonstrated human-level effectiveness in gaming environments their success in everyday tasks like visual navigation has been limited particularly under significant appearance variations. This limitation arises from (i) poor sample eff
56,4093,Robust Low Rank Kernel Embeddings of Multivariate Distributions,Le Song; Bo Dai,2013,NIPS 2013,main,Poster,,,0,17.365,0.000,,https://nips.cc/virtual/2013/poster/4093,https://papers.nips.cc/paper_files/paper/2013/file/49b8b4f95f02e055801da3b4f58e28b7-Paper.pdf,offline_nips,,"Kernel embedding of distributions has led to many recent advances in machine learning. However, latent and low rank structures prevalent in real world distributions have rarely been taken into account in this setting. Furthermore, no prior work in kernel embedding literature has addressed the issue "
57,6PcJEFKvBD,offline_rl_ope: A Python package for off-policy evaluation of offline RL models with real world data,Joshua William Spear; Matthieu Komorowski; REBECCA POPE; Neil J Sebire,2025,ICLR 2025,main,Reject,"infrastructure, software libraries, hardware, systems, etc.",Offline RL;OPE;Python;PyTorch,0,17.360,0.000,,https://openreview.net/forum?id=6PcJEFKvBD,,offline_iclr,,offline_rl_ope is a fully unit tested and runtime type checked Python package for performing off-policy evaluation of offline RL models. offline_rl_ope has been designed for OPE workflows using real world data by: naturally handling uneven trajectory lengths; including novel convergence metrics whic
58,BgcapX9ers,Hierarchical Object-Oriented POMDP Planning for Object Rearrangement,Rajesh Devaraddi Mangannavar; Alan Fern; Prasad Tadepalli,2025,ICLR 2025,main,Reject,"applications to robotics, autonomy, planning",rearrangement;POMDP;planning;reinforcement learning;object search,0,17.349,0.000,,https://openreview.net/forum?id=BgcapX9ers,,offline_iclr,,"We present an online planning framework for solving multi-object rearrangement problems in partially observable, multi-room environments. Current object rearrangement solutions, primarily based on Reinforcement Learning or hand-coded planning methods, often lack adaptability to diverse challenges. T"
59,09730,Hierarchical Relational Inference,Aleksandar Stanić; Sjoerd van Steenkiste; Jürgen Schmidhuber,2021,AAAI 2021,main,Technical,Machine Learning IV,,0,17.333,0.000,,https://aaai.org/papers/09730-hierarchical-relational-inference/,https://cdn.aaai.org/ojs/17170/17170-13-20664-1-2-20210518.pdf,offline_aaai,,"Common-sense physical reasoning in the real world requires learning about the interactions of objects and their dynamics. The notion of an abstract object, however, encompasses a wide variety of physical objects that differ greatly in terms of the complex behaviors they support. To address this, we "
60,W7WUJTGByR,Flow Equivariant World Modeling for Partially Observed Dynamic Environments,,2026,ICLR 2026,main,Active,generative models,World Model;Memory;Partial Observability;Equivariance;Structured Representation Learning,0,17.306,0.000,,https://openreview.net/forum?id=W7WUJTGByR,,offline_iclr,,"Embodied systems experience the world as 'a symphony of flows': a combination of many continuous streams of sensory input coupled to self-motion, interwoven with the motion of external objects. These streams obey smooth, time-parameterized symmetries, which combine through a precisely structured alg"
61,2024.naacl-long.302,Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models,Yujin Kim; Jaehong Yoon; Seonghyeon Ye; Sangmin Bae; Namgyu Ho,2024,NAACL 2024,main,Long,,,0,17.293,0.000,,https://aclanthology.org/2024.naacl-long.302/,https://aclanthology.org/2024.naacl-long.302.pdf,offline_naacl,,The dynamic nature of knowledge in an ever-changing world presents challenges for language models trained on static data; the model in the real world often requires not only acquiring new knowledge but also overwriting outdated information into updated ones. To study the ability of language models f
62,10161534,Open-vocabulary Queryable Scene Representations for Real World Planning,Boyuan Chen; Fei Xia; Brian Ichter; Kanishka Rao; Keerthana Gopalakrishnan,2023,ICRA 2023,main,Poster,,,0,17.281,0.000,,https://ieeexplore.ieee.org/document/10161534/,,offline_icra,,"Large language models (LLMs) have unlocked new capabilities of task planning from human instructions. However, prior attempts to apply LLMs to real-world robotic tasks are limited by the lack of grounding in the surrounding scene. In this paper, we develop NLMap, an open-vocabulary and queryable sce"
63,b2u1yrTwFK,Dyn-O: Building Structured World Models with Object-Centric Representations,Zizhao Wang; Kaixin Wang; Li Zhao; Peter Stone; Jiang Bian,2025,NIPS 2025,main,Poster,reinforcement_learning,World Model;Object-centric representation,0,17.227,0.000,,https://openreview.net/forum?id=b2u1yrTwFK,,offline_nips,,"World models aim to capture the dynamics of the environment, enabling agents to predict and plan for future states. In most scenarios of interest, the dynamics are highly centered on interactions among objects within the environment. This motivates the development of world models that operate on obj"
64,2023.findings-acl.579,World Models for Math Story Problems,Andreas Opedal; Niklas Stoehr; Abulhair Saparov; Mrinmaya Sachan,2023,ACL 2023,main,Findings,,,0,17.220,0.000,,https://aclanthology.org/2023.findings-acl.579/,https://aclanthology.org/2023.findings-acl.579.pdf,offline_acl,,"Solving math story problems is a complex task for students and NLP models alike, requiring them to understand the world as described in the story and reason over it to compute an answer. Recent years have seen impressive performance on automatically solving these problems with large pre-trained lang"
65,8593935,KnowRobSIM — Game Engine-Enabled Knowledge Processing Towards Cognition-Enabled Robot Control,Andrei Haidu; Daniel Beßler; Asil Kaan Bozcuoğlu; Michael Beetz; Andrei Haidu,2018,IROS 2018,main,Poster,,,0,17.190,0.000,,https://ieeexplore.ieee.org/document/8593935/,,offline_iros,,AI knowledge representation and reasoning methods consider actions to be blackboxes that abstract away from how they are executed. This abstract view does not suffice for the decision making capabilities required by robotic agents that are to accomplish manipulation tasks. Such robots have to reason
66,GfVKK5sKit,LLMs Struggle to Balance Reasoning and World Knowledge in Causal Narrative Understanding,,2026,ICLR 2026,main,Active,"foundation or frontier models, including LLMs",Causal Inference;Large Language Models;Reasoning;Narratives,0,17.187,0.000,,https://openreview.net/forum?id=GfVKK5sKit,,offline_iclr,,"The ability to robustly identify causal relationships is essential for autonomous decision-making and adaptation to novel scenarios. However, accurately inferring causal structure requires integrating both world knowledge and abstract logical reasoning. In this work, we investigate the interaction b"
67,9981158,Discover Life Skills for Planning as Bandits via Observing and Learning How the World Works,Tin Lai; Tin Lai,2022,IROS 2022,main,Poster,,,0,17.180,0.000,,https://ieeexplore.ieee.org/document/9981158/,,offline_iros,,We propose a novel approach for planning agents to compose abstract skills via observing and learning from historical interactions with the world. Our framework operates in a Markov state-space model via a set of actions under unknown pre-conditions. We formulate skills as high-level abstract polici
68,2022.emnlp-main.433,Retrofitting Multilingual Sentence Embeddings with Abstract Meaning Representation,Deng Cai; Xin Li; Jackie Chun-Sing Ho; Lidong Bing; Wai Lam,2022,EMNLP 2022,main,Main,,,0,17.179,0.000,,https://aclanthology.org/2022.emnlp-main.433/,https://aclanthology.org/2022.emnlp-main.433.pdf,offline_emnlp,,"We introduce a new method to improve existing multilingual sentence embeddings with Abstract Meaning Representation (AMR). Compared with the original textual input, AMR is a structured semantic representation that presents the core concepts and relations in a sentence explicitly and unambiguously. I"
69,34038,CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning,Yang Yue; Yulin Wang; Chenxin Tao; Pan Liu; Shiji Song,2025,CVPR 2025,main,Poster,,,0,17.160,0.000,,https://cvpr.thecvf.com/virtual/2025/poster/34038,https://openaccess.thecvf.com/content/CVPR2025/papers/Yue_CheXWorld_Exploring_Image_World_Modeling_for_Radiograph_Representation_Learning_CVPR_2025_paper.pdf,offline_cvpr,,"Humans can develop internal world models that encode common sense knowledge, telling them how the world works and predicting the consequences of their actions. This concept has emerged as a promising direction for establishing general-purpose machine-learning models in recent preliminary works, e.g."
70,2023.findings-acl.871,Improving Long Dialogue Summarization with Semantic Graph Representation,Yilun Hua; Zhaoyuan Deng; Kathleen McKeown,2023,ACL 2023,main,Findings,,,0,17.140,0.000,,https://aclanthology.org/2023.findings-acl.871/,https://aclanthology.org/2023.findings-acl.871.pdf,offline_acl,,"Although Large Language Models (LLMs) are successful in abstractive summarization of short dialogues, summarization of long dialogues remains challenging. To address this challenge, we propose a novel algorithm that processes complete dialogues comprising thousands of tokens into topic-segment-level"
71,article-30002,Abstract Action Scheduling for Optimal Temporal Planning via OMT,Stefan Panjkovic; Andrea Micheli,2024,AAAI 2024,main,Technical,planning routing and scheduling,,0,17.130,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/30002,https://ojs.aaai.org/index.php/AAAI/article/view/30002/31758,offline_aaai,,"Given the model of a system with explicit temporal constraints, optimal temporal planning is the problem of finding a schedule of actions that achieves a certain goal while optimizing an objective function. Recent approaches for optimal planning reduce the problem to a series of queries to an Optimi"
72,6094806,Comparison of several image features for WCE video abstract,Baopu Li; Max Q.-H. Meng; Baopu Li; Max Q.-H. Meng,2011,IROS 2011,main,Poster,,,0,17.128,0.000,,https://ieeexplore.ieee.org/document/6094806/,,offline_iros,,"The direct view of the inner tract of the small intestine is not feasible until a recently revolutionary imaging technology, wireless capsule endoscopy (WCE), appeared in 2001. However, interpretation of the produced video data for the digestive tract on each patient is left to naked eyes of medical"
73,2025.acl-long.1540,Deliberate Reasoning in Language Models as Structure-Aware Planning with an Accurate World Model,Siheng Xiong; Ali Payani; Yuan Yang; Faramarz Fekri,2025,ACL 2025,main,Long,,,0,17.122,0.000,,https://aclanthology.org/2025.acl-long.1540/,https://aclanthology.org/2025.acl-long.1540.pdf,offline_acl,,"Enhancing the reasoning capabilities of language models (LMs) remains a key challenge, especially for tasks that require complex, multi-step decision-making where existing Chain-of-Thought (CoT) approaches struggle with consistency and verification. In this paper, we propose a novel reasoning framew"
74,2023.acl-short.57,Learning Neuro-Symbolic World Models with Conversational Proprioception,Don Joven Agravante; Daiki Kimura; Michiaki Tatsubori; Asim Munawar; Alexander Gray,2023,ACL 2023,main,Short,,,0,17.121,0.000,,https://aclanthology.org/2023.acl-short.57/,https://aclanthology.org/2023.acl-short.57.pdf,offline_acl,,"The recent emergence of Neuro-Symbolic Agent (NeSA) approaches to natural language-based interactions calls for the investigation of model-based approaches. In contrast to model-free approaches, which existing NeSAs take, learning an explicit world model has an interesting potential especially in th"
75,2025.findings-acl.63,GlyphPattern: An Abstract Pattern Recognition for Vision-Language Models,Zixuan Wu; Yoolim Kim; Carolyn Jane Anderson,2025,ACL 2025,main,finding,,,0,17.118,0.000,,https://aclanthology.org/2025.findings-acl.63/,https://aclanthology.org/2025.findings-acl.63.pdf,offline_acl,,"Vision-Language Models (VLMs) have made rapid progress in reasoning across visual and textual data. While VLMs perform well on vision tasks that they are trained on, our results highlight key challenges in abstract pattern recognition. We present GlyphPattern, a 954 item dataset that pairs 318 human"
76,2024.lrec-main.433,DGoT: Dynamic Graph of Thoughts for Scientific Abstract Generation,Xinyu Ning; Yutong Zhao; Yitong Liu; Hongwen Yang,2024,COLING 2024,main,Main,,,0,17.101,0.000,,https://aclanthology.org/2024.lrec-main.433/,https://aclanthology.org/2024.lrec-main.433.pdf,offline_coling,,"The method of training language models based on domain datasets has obtained significant achievements in the task of generating scientific paper abstracts. However, such models face problems of generalization and expensive training costs. The use of large language models (LLMs) to solve the task of "
77,b557149a70,Bayesian Sparse Representation for Hyperspectral Image Super Resolution,Naveed Akhtar; Faisal Shafait; Ajmal Mian,2015,CVPR 2015,main,Poster,,,0,17.092,0.000,,https://openaccess.thecvf.com/content_cvpr_2015/html/Akhtar_Bayesian_Sparse_Representation_2015_CVPR_paper.html,https://openaccess.thecvf.com/content_cvpr_2015/papers/Akhtar_Bayesian_Sparse_Representation_2015_CVPR_paper.pdf,offline_cvpr,,"Despite the proven efficacy of hyperspectral imaging in many computer vision tasks, its widespread use is hindered by its low spatial resolution, resulting from hardware limitations. We propose a hyperspectral image super resolution approach that fuses a high resolution image with the low resolution"
78,LFCSVVIy1x,Can World Models Benefit VLMs for World Dynamics?,,2026,ICLR 2026,main,Active,"applications to computer vision, audio, language, and other modalities",World Model;Multi-modal Large Language Model;Multi-modal Representation Learning,0,17.083,0.000,,https://openreview.net/forum?id=LFCSVVIy1x,,offline_iclr,,"Trained on internet-scale video data, world models are increasingly recognized as powerful world simulators that can generate consistent and plausible dynamics over structure, motion, and physics. While recent studies have explored the few-shot learning capabilities of world models on vision tasks, "
79,DeG07_TcZvT,Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task,Kenneth Li; Aspen K Hopkins; David Bau; Fernanda Viégas; Hanspeter Pfister,2023,ICLR 2023,main,Top-5%,,world representation;GPT,0,17.071,0.000,,https://iclr.cc/virtual/2023/poster/11827,https://openreview.net/pdf?id=DeG07_TcZvT,offline_iclr,,"Language models show a surprising range of capabilities, but the source of their apparent competence is unclear. Do these networks just memorize a collection of surface statistics, or do they rely on internal representations of the process that generates the sequences they see? We investigate this q"
80,OFF38XvszP,Slot Structured World Models,Jonathan Collu; Riccardo Majellaro; Aske Plaat; Thomas M. Moerland,2024,ICLR 2024,main,Withdraw,reinforcement learning,world models;model-based reinforcement learning;object-centric representation learning,0,17.054,0.000,,https://openreview.net/forum?id=OFF38XvszP,,offline_iclr,,The ability to perceive and reason about individual objects enables humans to build a robust understanding of the environment and its dynamics. Replicating such abilities in artificial systems would represent a significant milestone toward building intelligent agents. Contrastive Learning of Structu
81,2022.emnlp-main.86,PLM-based World Models for Text-based Games,Minsoo Kim; Yeonjoon Jung; Dohyeon Lee; Seung-won Hwang,2022,EMNLP 2022,main,Main,,,0,17.043,0.000,,https://aclanthology.org/2022.emnlp-main.86/,https://aclanthology.org/2022.emnlp-main.86.pdf,offline_emnlp,,"World models have improved the ability of reinforcement learning agents to operate in a sample efficient manner, by being trained to predict plausible changes in the underlying environment. As the core tasks of world models are future prediction and commonsense understanding, our claim is that pre-t"
82,gehXu3kDU1P,Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning,Chi Zhang; Sirui Xie; Baoxiong Jia; Ying Nian Wu; Song-Chun Zhu,2022,ICLR 2022,main,Withdraw,,,0,17.026,0.000,,https://openreview.net/forum?id=gehXu3kDU1P,,offline_iclr,,"Is intelligence realized by connectionist or classicist? While connectionist approaches have achieved superhuman performance, there has been growing evidence that such task-specific superiority is particularly fragile in systematic generalization. This observation lies in the central debate (Fodor &"
83,UuchYL8wSZo,Learning Generalizable Visual Representations via Interactive Gameplay,Luca Weihs; Aniruddha Kembhavi; Kiana Ehsani; Sarah M Pratt; Winson Han,2021,ICLR 2021,main,Oral,,representation learning;deep reinforcement learning;computer vision,0,17.020,0.000,,https://iclr.cc/virtual/2021/poster/2685,https://openreview.net/pdf?id=UuchYL8wSZo,offline_iclr,,"A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in developing the neural flexibility for creative problem solving, decision making, and socialization. Comparatively littl"
84,jQSBcVURlpW,Learning Algebraic Representation for Abstract Spatial-Temporal Reasoning,Chi Zhang; Sirui Xie; Baoxiong Jia; Yixin Zhu; Ying Nian Wu,2021,ICLR 2021,main,Reject,,,0,17.011,0.000,,https://openreview.net/forum?id=jQSBcVURlpW,,offline_iclr,,"Is intelligence realized by connectionist or classicist? While connectionist approaches have achieved superhuman performance, there has been growing evidence that such task-specific superiority is particularly fragile in systematic generalization. This observation lies in the central debate (Fodor e"
85,2021.naacl-main.4,Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction,Zixuan Zhang; Heng Ji,2021,NAACL 2021,main,Long,,,0,16.968,0.000,,https://aclanthology.org/2021.naacl-main.4/,https://aclanthology.org/2021.naacl-main.4.pdf,offline_naacl,,"The tasks of Rich Semantic Parsing, such as Abstract Meaning Representation (AMR), share similar goals with Information Extraction (IE) to convert natural language texts into structured semantic representations. To take advantage of such similarity, we propose a novel AMR-guided framework for joint "
86,A6FGmwsH7x,ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games,Ruoyao Wang; Graham Todd; Xingdi Yuan; Ziang Xiao; Marc-Alexandre Côté,2023,EMNLP 2023,main,Long Main,,text games;code generation;simulation,0,16.956,0.000,,https://openreview.net/forum?id=A6FGmwsH7x,,offline_emnlp,,"In this work we investigate the capacity of language models to generate explicit, interpretable, and interactive world models of scientific and common-sense reasoning tasks.  We operationalize this as a task of generating text games, expressed as hundreds of lines of Python code.  To facilitate this"
87,G3IjhUERrD,CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks,Hoang H Nguyen; Ye Liu; Chenwei Zhang; TAO ZHANG; Philip S. Yu,2023,EMNLP 2023,main,Short Main,,large language model;natural language understanding;chain-of-thought;multi-step reasoning;slot filling;intent detection;semantic parsing;abstract meaning representation,0,16.923,0.000,,https://openreview.net/forum?id=G3IjhUERrD,,offline_emnlp,,"While Chain-of-Thought prompting is popular in reasoning tasks, its application to Large Language Models (LLMs) in Natural Language Understanding (NLU) is under-explored. Motivated by multi-step reasoning of LLMs, we propose Coarse-to-Fine Chain-of-Thought (CoF-CoT) approach that breaks down NLU tas"
88,2025.findings-acl.1337,Text2World: Benchmarking Large Language Models for Symbolic World Model Generation,Mengkang Hu; Tianxing Chen; Yude Zou; Yuheng Lei; Qiguang Chen,2025,ACL 2025,main,finding,,,0,16.918,0.000,,https://aclanthology.org/2025.findings-acl.1337/,https://aclanthology.org/2025.findings-acl.1337.pdf,offline_acl,,"Recently, there has been growing interest in leveraging large language models (LLMs) to generate symbolic world models from textual descriptions. Although LLMs have been extensively explored in the context of world modeling, prior studies encountered several challenges, including evaluation randomne"
89,6JJq5TW9Mc,Learning World Models with Identifiable Factorization,Yu-Ren Liu; Biwei Huang; Zhengmao Zhu; Honglong Tian; Mingming Gong,2023,NIPS 2023,main,Poster,,Model-based Reinforcement Learning; Causal Representation Learning;,0,16.884,0.000,,https://nips.cc/virtual/2023/poster/72763,https://openreview.net/pdf?id=6JJq5TW9Mc,offline_nips,,"Extracting a stable and compact representation of the environment is crucial for efficient reinforcement learning in high-dimensional, noisy, and non-stationary environments.  Different categories of information coexist in such environments -- how to effectively extract and disentangle the informati"
90,SJxrKgStDH,SCALOR: Generative World Models with Scalable Object Representations,Jindong Jiang*; Sepehr Janghorbani*; Gerard De Melo; Sungjin Ahn,2020,ICLR 2020,main,Poster,,,0,16.884,0.000,,https://openreview.net/forum?id=SJxrKgStDH,,offline_iclr,,"Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning. Most of the previous models have been shown to work only on scenes with a few objects. In this paper, we propose SCALOR, a probabilistic generative world model"
91,4399045,Automatic robot programming from learned abstract task knowledge,Steffen Knoop; Michael Pardowitz; Rudiger Dillmann; Steffen Knoop; Michael Pardowitz,2007,IROS 2007,main,Poster,,,0,16.879,0.000,,https://ieeexplore.ieee.org/document/4399045/,,offline_iros,,Robots with the capability of learning new tasks from humans need the ability to transform gathered abstract task knowledge into their own representation and dimensionality. New task knowledge that has been acquired e.g. with Programming by Demonstration approaches by observing a human does not a-pr
92,2024.findings-emnlp.167,A Notion of Complexity for Theory of Mind via Discrete World Models,X. Angelo Huang; Emanuele La Malfa; Samuele Marro; Andrea Asperti; Anthony G. Cohn,2024,EMNLP 2024,main,finding,,,0,16.863,0.000,,https://aclanthology.org/2024.findings-emnlp.167/,https://aclanthology.org/2024.findings-emnlp.167.pdf,offline_emnlp,,"Theory of Mind (ToM) can be used to assess the capabilities of Large Language Models (LLMs) in complex scenarios where social reasoning is required. While the research community has proposed many ToM benchmarks, their hardness varies greatly, and their complexity is not well defined. This work propo"
93,7DtgxVZGj-y,Contrastive Unsupervised Learning of World Model with Invariant Causal Features,Rudra P. K. Poudel; Harit Pandya; Roberto Cipolla,2023,ICLR 2023,main,Reject,,world models;causality;contrastive learning;model-based reinforcement learning;reinforcement learning;out-of-distribution generalisation;sim-to-real transfer;robot navigation,0,16.858,0.000,,https://openreview.net/forum?id=7DtgxVZGj-y,,offline_iclr,"We present a world model, which learns the causal features using invariance principle and achieves state-of-the-art performance on out-of-distribution generalisation.","In this paper we present a world model, which learns the causal features using invariance principle. We use contrastive unsupervised learning to learn the invariant causal features, which enforces invariance across augmentations of irrelevant parts or styles of the observation. Since the world model"
94,10801309,Abstraction of the Body Ability of the Transformer Robot System for the Transportation and Installation of Heavy Objects in Land and Underwater Environments,Tasuku Makabe; Kei Okada; Masayuki Inaba; Tasuku Makabe; Kei Okada,2024,IROS 2024,main,Poster,,,0,16.844,0.000,,https://ieeexplore.ieee.org/document/10801309/,,offline_iros,,"To give the single robot system the ability to realize many behaviors and to realize tasks with shifting environments and objectives, it is necessary to abstract the robot’s body ability to the extent that they can be detected by sensors in the body so that we can plan as the problem of state transi"
95,8594313,Learning Symbolic Representations for Planning with Parameterized Skills,Barrett Ames; Allison Thackston; George Konidaris; Barrett Ames; Allison Thackston,2018,IROS 2018,main,Poster,,,0,16.835,0.000,,https://ieeexplore.ieee.org/document/8594313/,,offline_iros,,"A critical capability required for generally intelligent robot behavior is the ability to sequence motor skills to reach a goal. This requires a (typically abstract) representation that supports goal-directed planning, which raises the question of how to construct such a representation. Previous wor"
96,UyLaqZ6PHA,How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances,Zihan Zhang; Meng Fang; Ling Chen; Mohammad Reza Namazi Rad; Jun Wang,2023,EMNLP 2023,main,Long Main,,large language models;survey;knowledge,0,16.826,0.000,,https://openreview.net/forum?id=UyLaqZ6PHA,,offline_emnlp,,"Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment. Maintaining their up-to-date status is a pressing concern in the current era. This paper provides a comprehensive review of recent advances in aligning deployed LLMs with the"
97,,Benchmarking Representation Learning for Natural World Image Collections,Grant Van Horn; Elijah Cole; Sara Beery; Kimberly Wilber; Serge Belongie,2021,CVPR 2021,main,Poster,,,0,16.800,0.000,,,https://openaccess.thecvf.com/content/CVPR2021/papers/Van_Horn_Benchmarking_Representation_Learning_for_Natural_World_Image_Collections_CVPR_2021_paper.pdf,offline_cvpr,,"Recent progress in self-supervised learning has resulted in models that are capable of extracting rich representations from image collections without requiring any explicit label supervision. However, to date the vast majority of these approaches have restricted themselves to training on standard be"
98,2022.emnlp-main.602,T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation,Anubhav Jangra; Preksha Nema; Aravindan Raghuveer,2022,EMNLP 2022,main,Main,,,0,16.799,0.000,,https://aclanthology.org/2022.emnlp-main.602/,https://aclanthology.org/2022.emnlp-main.602.pdf,offline_emnlp,,"Unavailability of parallel corpora for training text style transfer (TST) models is a very challenging yet common scenario. Also, TST models implicitly need to preserve the content while transforming a source sentence into the target style. To tackle these problems, an intermediate representation is"
99,r1e7NgrYvH,DO-AutoEncoder: Learning and Intervening Bivariate Causal Mechanisms in Images,Tianshuo Cong; Dan Peng; Furui Liu; Zhitang Chen,2020,ICLR 2020,main,Reject,,Causality discovery;AutoEncoder;Deep representation learning;Do-calculus,0,16.794,0.000,,https://openreview.net/forum?id=r1e7NgrYvH,,offline_iclr,We propose a new framework  for deep representation learning that fully capture bivariate causal relationship in the images.,"Some fundamental limitations of deep learning have been exposed such as lacking generalizability and being vunerable to adversarial attack. Instead, researchers realize that causation is much more stable than association relationship in data. In this paper, we propose a new framework called do-calcu"
100,article-28933,Abstraction of Situation Calculus Concurrent Game Structures,Yves Lesperance; Giuseppe De Giacomo; Maryam Rostamigiv; Shakil M. Khan,2024,AAAI 2024,main,Technical,knowledge representation and reasoning,,0,16.740,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/28933,https://ojs.aaai.org/index.php/AAAI/article/view/28933/29774,offline_aaai,,"We present a general framework for abstracting agent behavior in multi-agent synchronous games in the situation calculus, which provides a first-order representation of the state and allows us to model how plays depend on the data and objects involved.  We represent such games as action theories of "
101,8202309,DROAN — Disparity-space representation for obstacle AvoidaNce,Geetesh Dubey; Sankalp Arora; Sebastian Scherer; Geetesh Dubey; Sankalp Arora,2017,IROS 2017,main,Poster,,,0,16.731,0.000,,https://ieeexplore.ieee.org/document/8202309/,,offline_iros,,"Agile MAVs are required to operate in cluttered, unstructured environments at high speeds and low altitudes for efficient data gathering. Given the payload constraints and long range sensing requirements, cameras are the preferred sensing modality for MAVs. The computation burden of using cameras fo"
102,2024.lrec-main.1381,The ELCo Dataset: Bridging Emoji and Lexical Composition,Zi Yun Yang; Ziqing Zhang; Yisong Miao,2024,COLING 2024,main,Main,,,0,16.653,0.000,,https://aclanthology.org/2024.lrec-main.1381/,https://aclanthology.org/2024.lrec-main.1381.pdf,offline_coling,,"Can emojis be composed to convey intricate meanings like English phrases? As a pioneering study, we present the Emoji-Lexical Composition (ELCo) dataset, a new resource that offers parallel annotations of emoji sequences corresponding to English phrases. Our dataset contains 1,655 instances, spannin"
103,lReh4LaP8f,Structural Priming Demonstrates Abstract Grammatical Representations in Multilingual Language Models,James Michaelov; Catherine Arnett; Tyler A. Chang; Ben Bergen,2023,EMNLP 2023,main,Long Main,,abstraction;representation;multilingual language models;psychlinguistics;linguistic structure,0,16.632,0.000,,https://openreview.net/forum?id=lReh4LaP8f,,offline_emnlp,,"Abstract grammatical knowledge—of parts of speech and grammatical patterns—is key to the capacity for linguistic generalization in humans. But how abstract is grammatical knowledge in large language models? In the human literature, compelling evidence for grammatical abstraction comes from structura"
104,w50ICQC6QJ,Discovery of the Hidden World with Large Language Models,Chenxi Liu; Yongqiang Chen; Tongliang Liu; Mingming Gong; James Cheng,2024,NIPS 2024,main,Poster,causal_inference,Causal Discovery;Large Language Models;Causal Representation Learning,0,16.610,0.000,,https://neurips.cc/virtual/2024/poster/93175,https://openreview.net/pdf?id=w50ICQC6QJ,offline_nips,,"Revealing the underlying causal mechanisms in the real world is the key to the development of science. Despite the progress in the past decades, traditional causal discovery approaches (CDs) mainly rely on high-quality measured variables, usually given by human experts, to find causal relations. The"
105,yFGR36PLDJ,"Simple, Good, Fast: Self-Supervised World Models Free of Baggage",Jan Robine; Marc Höftmann; Stefan Harmeling,2025,ICLR 2025,main,Poster,reinforcement learning,Reinforcement learning;World models;Self-supervised learning;Atari 100k,0,16.593,0.000,,https://iclr.cc/virtual/2025/poster/27740,https://openreview.net/pdf?id=yFGR36PLDJ,offline_iclr,,"What are the essential components of world models? How far do we get with world models that are not employing RNNs, transformers, discrete representations, and image reconstructions? This paper introduces SGF, a Simple, Good, and Fast world model that uses self-supervised representation learning, ca"
106,aCHq10rQiH,CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models,Cheng Qian; Chi Han; Yi Fung; Yujia Qin; Zhiyuan Liu,2023,EMNLP 2023,main,Long Findings,,Large Language Models;Tool Creation;Model Reasoning,0,16.574,0.000,,https://openreview.net/forum?id=aCHq10rQiH,,offline_emnlp,,"Large Language Models (LLMs) have made significant progress in utilizing tools, but their ability is limited by API availability and the instability of implicit reasoning, particularly when both planning and execution are involved. To overcome these limitations, we propose CREATOR, a novel framework"
107,article-34081,Envisioning Class Entity Reasoning by Large Language Models for Few-shot Learning,Mushui Liu; Fangtai Wu; Bozheng Li; Ziqian Lu; Yunlong Yu,2025,AAAI 2025,main,Technical,machine learning iv,,0,16.569,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/34081,https://ojs.aaai.org/index.php/AAAI/article/view/34081/36236,offline_aaai,,"Few-shot learning (FSL) aims to recognize new concepts using a limited number of visual samples. Existing methods attempt to incorporate semantic information into the limited visual data for category understanding. However, these methods often enrich class-level feature representations with abstract"
108,article-25766,Abstract Argumentation Framework with Conditional Preferences,Gianvincenzo Alfano; Sergio Greco; Francesco Parisi; Irina Trubitsyna,2023,AAAI 2023,main,Technical,knowledge representation and reasoning,,0,16.558,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/25766,https://ojs.aaai.org/index.php/AAAI/article/view/25766/25538,offline_aaai,,"Dung's abstract Argumentation Framework (AF) has emerged as a central formalism in the area of knowledge representation and reasoning.
Preferences in AF allow to represent the comparative strength of arguments in a simple yet expressive way. 
Preference-based AF (PAF) has been proposed to extend AF "
109,2024.findings-emnlp.110,Abstraction-of-Thought Makes Language Models Better Reasoners,Ruixin Hong; Hongming Zhang; Xiaoman Pan; Dong Yu; Changshui Zhang,2024,EMNLP 2024,main,finding,,,0,16.556,0.000,,https://aclanthology.org/2024.findings-emnlp.110/,https://aclanthology.org/2024.findings-emnlp.110.pdf,offline_emnlp,,"Abstract reasoning, the ability to reason from the abstract essence of a problem, serves as a key to generalization in human reasoning. However, eliciting language models to perform reasoning with abstraction remains unexplored. This paper seeks to bridge this gap by introducing a novel structured r"
110,8594242,Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation,Craig Sherstan; Marlos C. Machado; Patrick M. Pilarski; Craig Sherstan; Marlos C. Machado,2018,IROS 2018,main,Poster,,,0,16.522,0.000,,https://ieeexplore.ieee.org/document/8594242/,,offline_iros,,"We propose using the Successor Representation (SR) to accelerate learning in a constructive knowledge system based on General Value Functions (GVFs). In real-world settings, like robotics for unstructured and dynamic environments, it is impossible to model all meaningful aspects of a system and its "
111,7orD38wzdi,Ego-centric Learning of Communicative World Models for Autonomous Driving,Hang Wang; Dechen Gao; Qiaoyi Fang; Junshan Zhang,2025,ICLR 2025,main,Reject,reinforcement learning,World Model;Reinforcement Learning;Autonomous Driving;Distributed Learning,0,16.517,0.000,,https://openreview.net/forum?id=7orD38wzdi,,offline_iclr,,"We study multi-agent reinforcement learning (MARL) for tasks in complex high-dimensional environments, such as autonomous driving. 
MARL is known to suffer from the *partial observability* and *non-stationarity* issues. To tackle these challenges, information sharing is often employed, which however"
112,03930,DANets: Deep Abstract Networks for Tabular Data Classification and Regression,Jintai Chen; Kuanlun Liao; Yao Wan; Danny Z. Chen; Jian Wu,2022,AAAI 2022,main,Technical,Data Mining and Knowledge Management,,0,16.517,0.000,,https://aaai.org/papers/03930-danets-deep-abstract-networks-for-tabular-data-classification-and-regression/,https://cdn.aaai.org/ojs/20309/20309-13-24322-1-2-20220628.pdf,offline_aaai,,"Tabular data are ubiquitous in real world applications. Although many commonly-used neural components (e.g., convolution) and extensible neural networks (e.g., ResNet) have been developed by the machine learning community, few of them were effective for tabular data and few designs were adequately t"
113,7354232,A novel approach based on commonsense knowledge representation and reasoning in open world for intelligent ambient assisted living services,N. Ayari; A. Chibani; Y. Amirat; E. T. Matson; N. Ayari,2015,IROS 2015,main,Poster,,,0,16.497,0.000,,https://ieeexplore.ieee.org/document/7354232/,,offline_iros,,"The next generation of ambient assisted living services will be based on eco-systems or organizations of intelligent artificial agents embodied in companion robots and smart objects. To provide, anywhere and anytime, smart assistance services to people, these agents need to be endowed with advanced "
114,10160488,TOP-JAM: A bio-inspired topology-based model of joint attention for human-robot interaction,Hendry Ferreira Chame; Aurélie Clodic; Rachid Alami; Hendry Ferreira Chame; Aurélie Clodic,2023,ICRA 2023,main,Poster,,,0,16.495,0.000,,https://ieeexplore.ieee.org/document/10160488/,,offline_icra,,"Coexisting with others and interacting in society implies sharing knowledge and attention about world objects, events, features, episodes, and even imagination or abstract ideas in time and space. Inspired by human phenomenological, cognitive and behavioral research, this work focuses on the study o"
115,2024.acl-long.106,LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin,Shihan Dou; Enyu Zhou; Yan Liu; Songyang Gao; Wei Shen,2024,ACL 2024,main,Long,,,0,16.456,0.000,,https://aclanthology.org/2024.acl-long.106/,https://aclanthology.org/2024.acl-long.106.pdf,offline_acl,,"Supervised fine-tuning (SFT) is a crucial step for large language models (LLMs), enabling them to align with human instructions and enhance their capabilities in downstream tasks. Substantially increasing instruction data is a direct solution to align the model with a broader range of downstream tas"
116,,Online Learning of Reusable Abstract Models for Object Goal Navigation,Tommaso Campari; Leonardo Lamanna; Paolo Traverso; Luciano Serafini; Lamberto Ballan,2022,CVPR 2022,main,Poster,,,0,16.355,0.000,,,https://openaccess.thecvf.com/content/CVPR2022/papers/Campari_Online_Learning_of_Reusable_Abstract_Models_for_Object_Goal_Navigation_CVPR_2022_paper.pdf,offline_cvpr,,"In this paper, we present a novel approach to incrementally learn an Abstract Model of an unknown environment, and show how an agent can reuse the learned model for tackling the Object Goal Navigation task. The Abstract Model is a finite state machine in which each state is an abstraction of a state"
117,article-25881,Exploiting Multiple Abstractions in Episodic RL via Reward Shaping,Roberto Cipollone; Giuseppe De Giacomo; Marco Favorito; Luca Iocchi; Fabio Patrizi,2023,AAAI 2023,main,Technical,machine learning i,,0,16.353,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/25881,https://ojs.aaai.org/index.php/AAAI/article/view/25881/25653,offline_aaai,,"One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy. To address this problem and improve learning efficiency, we consider a linear hierarchy of abstraction layers of the Markov Decision "
118,hWS4MueyzC,Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World,Rujie Wu; Xiaojian Ma; Zhenliang Zhang; Wei Wang; Qing Li,2024,ICLR 2024,main,Poster,datasets and benchmarks,Few-shot learning;Visual reasoning;Open world learning,0,16.336,0.000,,https://iclr.cc/virtual/2024/poster/18093,https://openreview.net/pdf?id=hWS4MueyzC,offline_iclr,,"We introduce Bongard-OpenWorld, a new benchmark for evaluating real-world few-shot reasoning for machine vision. It originates from the classical Bongard Problems (BPs): Given two sets of images (positive and negative), the model needs to identify the set that query images belong to by inducing the "
119,vC6DGcAdWR,Social World Models: Universal Structured Representations for Social Reasoning,,2026,ICLR 2026,main,Active,"neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)",social intelligence; theory of mind; world model,0,16.332,0.000,,https://openreview.net/forum?id=vC6DGcAdWR,,offline_iclr,,"Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited information. In contrast, AI systems struggle to automatically structure and reason about these implicit social contexts, largely due to traditional input repre"
120,4059059,A Programming Framework Supporting An Ethology-based Behavior Control Architecture,Sanghoon Lee; Il Hong Suh; Sanghoon Lee; Il Hong Suh,2006,IROS 2006,main,Poster,,,0,16.297,0.000,,https://ieeexplore.ieee.org/document/4059059/,,offline_iros,,"A robot programming language (PLEASE) is to be proposed together with an ethology-based action-selection (EASE) architecture, where following features are supported; Hierarchical tree-structured behavior organization, layertailored arbiter programming, abstract expression of real world situation by "
121,9e9wHUkC8Q,MANAR: Memory-augmented Attention with Navigational Abstract conceptual Representation,,2026,ICLR 2026,main,Active,"other topics in machine learning (i.e., none of the above)",brain inspired;memory-augmented architecture;attention;out-of-the-box thinking;imagenet;librispeech;quadratic complexity,0,16.288,0.000,,https://openreview.net/forum?id=9e9wHUkC8Q,,offline_iclr,,"Transformers - and their multi-head attention (MHA) core - power today's leading models across a broad application spectrum. Yet MHA contextualizes each token through explicit, pair-wise interactions with every other token, yielding quadratic time/space cost and an unbounded, linearly-growing contex"
122,2021.naacl-main.435,Do RNN States Encode Abstract Phonological Alternations?,Miikka Silfverberg; Francis Tyers; Garrett Nicolai; Mans Hulden,2021,NAACL 2021,main,Long,,,0,16.272,0.000,,https://aclanthology.org/2021.naacl-main.435/,https://aclanthology.org/2021.naacl-main.435.pdf,offline_naacl,,"Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data. Despite the performance, the opacity of neural models makes it difficult to determine whether "
123,Bkp_y7qxe,Unsupervised Deep Learning of State Representation Using Robotic Priors,Timothee LESORT; David FILLIAT,2017,ICLR 2017,main,Reject,,Deep learning;Computer vision;Unsupervised Learning,0,16.267,0.000,,https://openreview.net/forum?id=Bkp_y7qxe,,offline_iclr,This paper introduces a method for training a deep neural network to learn a  representation of a robot's environment state using a priori knowledge.,"Our understanding of the world depends highly on how we represent it.  Using background knowledge about its complex underlying physical rules, our brain can produce intuitive and simplified representations which it can easily use to solve problems. The approach of this paper aims to reproduce this s"
124,2024.emnlp-industry.21,Code Representation Pre-training with Complements from Program Executions,Jiabo Huang; Jianyu Zhao; Yuyang Rong; Yiwen Guo; Yifeng He,2024,EMNLP 2024,main,Industry,,,0,16.259,0.000,,https://aclanthology.org/2024.emnlp-industry.21/,https://aclanthology.org/2024.emnlp-industry.21.pdf,offline_emnlp,,"Language models for natural language processing have been grafted onto programming language modeling for advancing code intelligence. Although it can be represented in the text format, code is syntactically more rigorous, as it is designed to be properly compiled or interpreted to perform a set of b"
125,7353774,Integrating physics-based prediction with Semantic plan Execution Monitoring,Sebastian Rockel; Štefan Konečný; Sebastian Stock; Joachim Hertzberg; Federico Pecora,2015,IROS 2015,main,Poster,,,0,16.215,0.000,,https://ieeexplore.ieee.org/document/7353774/,,offline_iros,,"Real-world robotic systems have to perform reliably in uncertain and dynamic environments. State-of-the-art cognitive robotic systems use an abstract symbolic representation of the real world for high-level reasoning. Some aspects of the world, such as object dynamics, are inherently difficult to ca"
126,2022.findings-emnlp.427,Keyphrase Generation Beyond the Boundaries of Title and Abstract,Krishna Garg; Jishnu Ray Chowdhury; Cornelia Caragea,2022,EMNLP 2022,main,finding,,,0,16.182,0.000,,https://aclanthology.org/2022.findings-emnlp.427/,https://aclanthology.org/2022.findings-emnlp.427.pdf,offline_emnlp,,"Keyphrase generation aims at generating important phrases (keyphrases) that best describe a given document. In scholarly domains, current approaches have largely used only the title and abstract of the articles to generate keyphrases. In this paper, we comprehensively explore whether the integration"
127,FKNtgr0qQy,Emergence of Abstract State Representations in Embodied Sequence Modeling,Tian Yun; Zilai Zeng; Kunal Handa; Ashish V Thapliyal; Bo Pang,2023,EMNLP 2023,main,Long Main,,Interpretability and Analysis; Decision Making via Sequence Modeling; Language Grounding to Vision and Beyond,0,16.178,0.000,,https://openreview.net/forum?id=FKNtgr0qQy,,offline_emnlp,,"Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promising performance, it remains unclear if embodied sequence modeling leads to the emergence of internal representations that"
128,2024.acl-short.1,Can Language Models Serve as Text-Based World Simulators?,Ruoyao Wang; Graham Todd; Ziang Xiao; Xingdi Yuan; Marc-Alexandre Côté,2024,ACL 2024,main,Short,,,0,16.137,0.000,,https://aclanthology.org/2024.acl-short.1/,https://aclanthology.org/2024.acl-short.1.pdf,offline_acl,,"Virtual environments play a key role in benchmarking advances in complex planning and decision-making tasks but are expensive and complicated to build by hand. Can current language models themselves serve as world simulators, correctly predicting how actions change different world states, thus bypas"
129,5650146,CRAM — A Cognitive Robot Abstract Machine for everyday manipulation in human environments,Michael Beetz; Lorenz Mösenlechner; Moritz Tenorth; Michael Beetz; Lorenz Mösenlechner,2010,IROS 2010,main,Poster,,,0,16.118,0.000,,https://ieeexplore.ieee.org/document/5650146/,,offline_iros,,"This paper describes CRAM (Cognitive Robot Abstract Machine) as a software toolbox for the design, the implementation, and the deployment of cognition-enabled autonomous robots performing everyday manipulation activities. CRAM equips autonomous robots with lightweight reasoning mechanisms that can i"
130,article-26017,A Data Source for Reasoning Embodied Agents,Jack Lanchantin; Sainbayar Sukhbaatar; Gabriel Synnaeve; Yuxuan Sun; Kavya Srinet,2023,AAAI 2023,main,Technical,machine learning ii,,0,16.096,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/26017,https://ojs.aaai.org/index.php/AAAI/article/view/26017/25789,offline_aaai,,"Recent progress in using machine learning models for reasoning tasks has been driven by novel model architectures, large-scale pre-training protocols, and dedicated reasoning datasets for fine-tuning.  In this work, to further pursue these advances, we introduce a new data generator for machine reas"
131,,WireRoom: Model-guided Explorative Design of Abstract Wire Art,Zhijin Yang; Pengfei Xu; Hongbo Fu; Hui Huang,2021,SIGGRAPH 2021,main,Technical Paper,,,0,16.015,0.000,,,,offline_siggraph,,
132,article-27921,Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection,Thang Doan; Xin Li; Sima Behpour; Wenbin He; Liang Gou,2024,AAAI 2024,main,Technical,computer vision i,,0,15.945,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/27921,https://ojs.aaai.org/index.php/AAAI/article/view/27921/27864,offline_aaai,,"Open World Object Detection (OWOD) is a challenging and realistic task that extends beyond the scope of standard Object Detection task. It involves detecting both known and unknown objects while integrating learned knowledge for future tasks. However, the level of ""unknownness"" varies significantly "
133,2024.emnlp-main.1072,Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model,Wenqi Zhang; Zhenglin Cheng; Yuanyu He; Mengna Wang; Yongliang Shen,2024,EMNLP 2024,main,Main,,,0,15.936,0.000,,https://aclanthology.org/2024.emnlp-main.1072/,https://aclanthology.org/2024.emnlp-main.1072.pdf,offline_emnlp,,"Although most current large multimodal models (LMMs) can already understand photos of natural scenes and portraits, their understanding of abstract images, e.g., charts, maps, or layouts, and visual reasoning capabilities remains quite rudimentary. They often struggle with simple daily tasks, such a"
134,2022.naacl-main.425,What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured,Alexander Henlein; Alexander Mehler,2022,NAACL 2022,main,Long,,,0,15.917,0.000,,https://aclanthology.org/2022.naacl-main.425/,https://aclanthology.org/2022.naacl-main.425.pdf,offline_naacl,,Transformer-based models are now predominant in NLP.They outperform approaches based on static models in many respects. This success has in turn prompted research that reveals a number of biases in the language models generated by transformers. In this paper we utilize this research on biases to inv
135,2021.findings-emnlp.34,"WHOSe Heritage: Classification of UNESCO World Heritage Statements of ""Outstanding Universal Value” with Soft Labels",Nan Bai; Renqian Luo; Pirouz Nourian; Ana Pereira Roders,2021,EMNLP 2021,main,finding,,,0,15.907,0.000,,https://aclanthology.org/2021.findings-emnlp.34/,https://aclanthology.org/2021.findings-emnlp.34.pdf,offline_emnlp,,"The UNESCO World Heritage List (WHL) includes the exceptionally valuable cultural and natural heritage to be preserved for mankind. Evaluating and justifying the Outstanding Universal Value (OUV) is essential for each site inscribed in the WHL, and yet a complex task, even for experts, since the sel"
136,2021.acl-long.342,Semantic Representation for Dialogue Modeling,Xuefeng Bai; Yulong Chen; Linfeng Song; Yue Zhang,2021,ACL 2021,main,Long,,,0,15.895,0.000,,https://aclanthology.org/2021.acl-long.342/,https://aclanthology.org/2021.acl-long.342.pdf,offline_acl,,"Although neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities. To this end, we exploit Abstract Meaning Representation (AMR) to help dialogue modeling. Compared with the textual input,"
137,2022.findings-emnlp.397,Baked-in State Probing,Shubham Toshniwal; Sam Wiseman; Karen Livescu; Kevin Gimpel,2022,EMNLP 2022,main,finding,,,0,15.894,0.000,,https://aclanthology.org/2022.findings-emnlp.397/,https://aclanthology.org/2022.findings-emnlp.397.pdf,offline_emnlp,,Neural language models have been analyzed for their linguistic and extra-linguistic knowledge via probing. Of particular interest has been the following question: how much can a language model trained only on form learn about meaning? Recent work has demonstrated via probing classifiers that in the 
138,2024.acl-long.637,Can Large Language Models Interpret Noun-Noun Compounds? A Linguistically-Motivated Study on Lexicalized and Novel Compounds,Giulia Rambelli; Emmanuele Chersoni; Claudia Collacciani; Marianna Bolognesi,2024,ACL 2024,main,Long,,,0,15.812,0.000,,https://aclanthology.org/2024.acl-long.637/,https://aclanthology.org/2024.acl-long.637.pdf,offline_acl,,"Noun-noun compounds interpretation is the task where a model is given one of such constructions, and it is asked to provide a paraphrase, making the semantic relation between the nouns explicit, as in carrot cake is “a cake made of carrots.” Such a task requires the ability to understand the implici"
139,2024.naacl-long.209,Analyzing the Role of Semantic Representations in the Era of Large Language Models,Zhijing Jin; Yuen Chen; Fernando Gonzalez Adauto; Jiarui Liu; Jiayi Zhang,2024,NAACL 2024,main,Long,,,0,15.794,0.000,,https://aclanthology.org/2024.naacl-long.209/,https://aclanthology.org/2024.naacl-long.209.pdf,offline_naacl,,"Traditionally, natural language processing (NLP) models often use a rich set of features created by linguistic expertise, such as semantic representations. However, in the era of large language models (LLMs), more and more tasks are turned into generic, end-to-end sequence generation problems. In th"
140,2025.naacl-long.3,World Models with Hints of Large Language Models for Goal Achieving,Zeyuan Liu; Ziyu Huan; Xiyao Wang; Jiafei Lyu; Jian Tao,2025,NAACL 2025,main,Long,,,0,15.781,0.000,,https://aclanthology.org/2025.naacl-long.3/,https://aclanthology.org/2025.naacl-long.3.pdf,offline_naacl,,"Reinforcement learning struggles in the face of long-horizon tasks and sparse goals due to the difficulty in manual reward specification. While existing methods address this by adding intrinsic rewards, they may fail to provide meaningful guidance in long-horizon decision-making tasks with large sta"
141,article-28918,Redefining ABA+ Semantics via Abstract Set-to-Set Attacks,Yannis Dimopoulos; Wolfgang Dvorak; Matthias König; Anna Rapberger; Markus Ulbricht,2024,AAAI 2024,main,Technical,knowledge representation and reasoning,,0,15.744,0.000,,https://ojs.aaai.org/index.php/AAAI/article/view/28918,https://ojs.aaai.org/index.php/AAAI/article/view/28918/29747,offline_aaai,,"Assumption-based argumentation (ABA) is a powerful defeasible reasoning formalism which is based on the interplay of assumptions, their contraries, and inference rules. ABA with preferences (ABA+) generalizes the basic model by allowing qualitative comparison between assumptions. The integration of "
142,10801944,Domain Randomization-free Sim-to-Real : An Attention-Augmented Memory Approach for Robotic Tasks,Jia Qu; Shun Otsubo; Tomoya Yamanokuchi; Takamitsu Matsubara; Shotaro Miwa,2024,IROS 2024,main,Poster,,,0,15.720,0.000,,https://ieeexplore.ieee.org/document/10801944/,,offline_iros,,"The sim-to-real gap, a long-standing challenge in the field of robotics, has garnered significant attention. Essentially, it is important to learn robust representation models that can be seamlessly applied in both simulation and real world. Traditional approaches like domain randomization have demo"
143,8967717,Learning Physics-Based Manipulation in Clutter: Combining Image-Based Generalization and Look-Ahead Planning,Wissam Bejjani; Mehmet R. Dogar; Matteo Leonetti; Wissam Bejjani; Mehmet R. Dogar,2019,IROS 2019,main,Poster,,,0,15.609,0.000,,https://ieeexplore.ieee.org/document/8967717/,,offline_iros,,"Physics-based manipulation in clutter involves complex interaction between multiple objects. In this paper, we consider the problem of learning, from interaction in a physics simulator, manipulation skills to solve this multi-step sequential decision making problem in the real world. Our approach ha"
144,6696426,Selective exploration exploiting skills in hierarchical reinforcement learning framework,Gakuto Masuyama; Atsushi Yamashita; Hajime Asama; Gakuto Masuyama; Atsushi Yamashita,2013,IROS 2013,main,Poster,,,0,15.558,0.000,,https://ieeexplore.ieee.org/document/6696426/,,offline_iros,,"In this paper, novel reinforcement learning method with intrinsic motivation for reproducibility of the past successful experience is presented. The experience is extracted as skill, which is composed of action sequence and abstract knowledge about observed sensor input. Utilizing the collected skil"
145,9635937,An Efficient and Continuous Representation for Occupancy Mapping with Random Mapping,Xu Liu; Decai Li; Yuqing He; Xu Liu; Decai Li,2021,IROS 2021,main,Poster,,,0,15.548,0.000,,https://ieeexplore.ieee.org/document/9635937/,,offline_iros,,"Generating meaningful spatial models of physical environments is a crucial ability for autonomous navigation of mobile robots. This paper considers the problem of building continuous occupancy maps from sparse and noisy sensor data. To this end, we propose a new method named random mapping maps that"
146,05692,Conditional Abstract Dialectical Frameworks,Jesse Heyninck; Matthias Thimm; Gabriele Kern-Isberner; Tjitze Rienstra; Kenneth Skiba,2022,AAAI 2022,main,Technical,Knowledge Representation and Reasoning,,0,15.531,0.000,,https://aaai.org/papers/05692-conditional-abstract-dialectical-frameworks/,https://cdn.aaai.org/ojs/20511/20511-13-24524-1-2-20220628.pdf,offline_aaai,,"Abstract dialectical frameworks (in short, ADFs) are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. This idea is generalized by letting acceptance conditions being assigned to complex f"
147,GTzP2GC7NR,When SNN meets ANN: Error-Free ANN-to-SNN Conversion for Extreme Edge Efficiency,Gourav Datta; Zeyu Liu; James Diffenderfer; Bhavya Kailkhura; Peter Anthony Beerel,2025,ICLR 2025,main,Withdraw,"other topics in machine learning (i.e., none of the above)",SNN;ANN-to-SNN conversion;IF model;ImageNet;spiking activity,0,15.507,0.000,,https://openreview.net/forum?id=GTzP2GC7NR,,offline_iclr,,"Spiking Neural Networks (SNN) are now demonstrating comparable accuracy to convolutional neural networks (CNN), thanks to advanced ANN-to-SNN conversion techniques, all while delivering remarkable energy and latency efficiency when deployed on neuromorphic hardware. However, these conversion techniq"
148,Qr9TjKYzjl,Small features matter: Robust representation for world models,Zarif Ikram; Miranda Anna Christ; Ling Pan; Dianbo Liu,2025,ICLR 2025,main,Reject,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",Representation learning;model based reinforcement learning;world models,0,15.450,0.000,,https://openreview.net/forum?id=Qr9TjKYzjl,,offline_iclr,,"In Model-Based Reinforcement Learning (MBRL), an agent learns to make decisions by building a world model that predicts the environment's dynamics. The accuracy of this world model is crucial for generalizability and sample efficiency. Many works rely on pixel-level reconstruction, which may focus o"
149,5980219,Two level world modeling for cooperating robots using a multiple hypotheses filter,J. Elfring; M.J.G. van de Molengraft; R.J.M. Janssen; M. Steinbuch; J. Elfring,2011,ICRA 2011,main,Poster,,,0,15.430,0.000,,https://ieeexplore.ieee.org/document/5980219/,,offline_icra,,"Robots increasingly operate in dynamic environments and in order to operate safely, reliable world models are indispensable. A world model is the robot's view of the world and contains information about obstacle locations and velocities. A two level algorithm is proposed. It is of particular use for"
150,9636830,OPEn: An Open-ended Physics Environment for Learning Without a Task,Chuang Gan; Abhishek Bhandwaldar; Antonio Torralba; Joshua B. Tenenbaum; Phillip Isola,2021,IROS 2021,main,Poster,,,0,15.416,0.000,,https://ieeexplore.ieee.org/document/9636830/,,offline_iros,,"Humans have mental models that allow them to plan, experiment, and reason in the physical world. How should an intelligent agent go about learning such models? In this paper, we will study if models of the world learned in an open-ended physics environment, without any specific tasks, can be reused "
151,9811652,Exploiting Abstract Symmetries in Reinforcement Learning for Complex Environments,Kashish Gupta; Homayoun Najjaran; Kashish Gupta; Homayoun Najjaran,2022,ICRA 2022,main,Poster,,,0,15.414,0.000,,https://ieeexplore.ieee.org/document/9811652/,,offline_icra,,"Reinforcement Learning is rapidly establishing itself as the foremost choice for optimization of sequential autonomous decision-making problems. Encumbered by its sample inefficiency, the extension of the field to large state space and dynamic environments remains an open problem. We present a novel"
152,6907396,Spectral analysis for long-term robotic mapping,Tomas Krajnik; Jaime Pulido Fentanes; Grzegorz Cielniak; Christian Dondrup; Tom Duckett,2014,ICRA 2014,main,Poster,,,0,15.394,0.000,,https://ieeexplore.ieee.org/document/6907396/,,offline_icra,,"This paper presents a new approach to mobile robot mapping in long-term scenarios. So far, the environment models used in mobile robotics have been tailored to capture static scenes and dealt with the environment changes by means of `memory decay'. While these models keep up with slowly changing env"
153,5652268,Programming by demonstration of probabilistic decision making on a multi-modal service robot,Sven R. Schmidt-Rohr; Martin Lösch; Rainer Jäkel; Rüdiger Dillmann; Sven R. Schmidt-Rohr,2010,IROS 2010,main,Poster,,,0,15.345,0.000,,https://ieeexplore.ieee.org/document/5652268/,,offline_iros,,"In this paper we propose a process which is able to generate abstract service robot mission representations, utilized during execution for autonomous, probabilistic decision making, by observing human demonstrations. The observation process is based on the same perceptive components as used by the r"
154,10160337,Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose Estimation,Binqian Jiang; Shaojie Shen; Binqian Jiang; Shaojie Shen,2023,ICRA 2023,main,Poster,,,0,15.344,0.000,,https://ieeexplore.ieee.org/document/10160337/,,offline_icra,,"This paper proposes Contour Context, a simple, effective, and efficient topological loop closure detection pipeline with accurate 3-DoF metric pose estimation, targeting the urban autonomous driving scenario. We interpret the Cartesian bird's eye view (BEV) image projected from 3D LiDAR points as la"
155,01567,Stratified Rule-Aware Network for Abstract Visual Reasoning,Sheng Hu; Yuqing Ma; Xianglong Liu; Yanlu Wei; Shihao Bai,2021,AAAI 2021,main,Technical,Computer Vision I,,0,15.310,0.000,,https://aaai.org/papers/01567-stratified-rule-aware-network-for-abstract-visual-reasoning/,https://cdn.aaai.org/ojs/16248/16248-13-19742-1-2-20210518.pdf,offline_aaai,,"Abstract reasoning refers to the ability to analyze information, discover rules at an intangible level, and solve problems in innovative ways. Raven's Progressive Matrices (RPM) test is typically used to examine the capability of abstract reasoning. The subject is asked to identify the correct choic"
156,imxSI4yUZo,Green Pruning: Layer Interdependence-Aware CNN Pruning for Resource Efficiency,Sadegh Tofigh; Mohammad Askarizadeh Khanaman; M. Omair Ahmad; M.N.S. Swamy; Kim Khoa Nguyen,2026,ICLR 2026,main,Withdraw,"alignment, fairness, safety, privacy, and societal considerations",Convolutional Neural Networks;Structured Filter Pruning;Model Compression Methods;Best Approximation;Resource Efficiency,0,15.290,0.000,,https://openreview.net/forum?id=imxSI4yUZo,,offline_iclr,,"The rising computational demands of pruning algorithms have heightened challenges about their energy consumption and carbon footprint in convolutional neural networks. We address these challenges from two perspectives. First, we introduce new evaluation metrics for pruning: a Resource Efficiency (RE"
157,6094822,Representation of manipulation-relevant object properties and actions for surprise-driven exploration,Susanne Petsch; Darius Burschka; Susanne Petsch; Darius Burschka,2011,IROS 2011,main,Poster,,,0,15.240,0.000,,https://ieeexplore.ieee.org/document/6094822/,,offline_iros,,We propose a framework for the sensor-based estimation of manipulation-relevant object properties and the abstraction of known actions in a learning setup from the observation of humans. The descriptors consists of an object-centric representation of manipulation constraints and a scene-specific act
158,E0cjqfM55C,Learning Interactive World Model for Object-Centric Reinforcement Learning,Fan Feng; Phillip Lippe; Sara Magliacane,2025,NIPS 2025,main,Poster,reinforcement_learning,World Model;Object-Centric RL,0,15.237,0.000,,https://openreview.net/forum?id=E0cjqfM55C,,offline_nips,,"Agents that understand objects and their interactions can learn policies that are more robust and transferable. However, most object-centric RL methods factor state by individual objects while leaving interactions implicit. We introduce the Factored Interactive Object-Centric World Model (FIOC-WM), "
159,ZNWpUfwisS,Adaptive Test-Time Compute Allocation via Query Complexity Estimation in Large Language Models,Yuhang Du,2026,ICLR 2026,main,Withdraw,"foundation or frontier models, including LLMs",Adaptive Compute Allocation 、Large Language Models 、Complexity Estimation 、Inference Efficiency 、Resource Optimization,0,15.227,0.000,,https://openreview.net/forum?id=ZNWpUfwisS,,offline_iclr,,"Recent advances in test-time compute scaling have demonstrated substantial performance improvements for large language models through increased inference-time computation. However, existing approaches uniformly allocate computational resources regardless of query complexity, leading to significant i"
160,9196582,Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video,Oier Mees; Markus Merklinger; Gabriel Kalweit; Wolfram Burgard; Oier Mees,2020,ICRA 2020,main,Poster,,,0,15.209,0.000,,https://ieeexplore.ieee.org/document/9196582/,,offline_icra,,"Key challenges for the deployment of reinforcement learning (RL) agents in the real world are the discovery, representation and reuse of skills in the absence of a reward function. To this end, we propose a novel approach to learn a task-agnostic skill embedding space from unlabeled multi-view video"
161,06496,Strong Explanations in Abstract Argumentation,Markus Ulbricht; Johannes P. Wallner,2021,AAAI 2021,main,Technical,Knowledge Representation and Reasoning,,0,15.203,0.000,,https://aaai.org/papers/06496-strong-explanations-in-abstract-argumentation/,https://cdn.aaai.org/ojs/16805/16805-13-20299-1-2-20210518.pdf,offline_aaai,,Abstract argumentation constitutes both a major research strand and a key approach that provides the core reasoning engine for a multitude of formalisms in computational argumentation in AI. Reasoning in abstract argumentation is carried out by viewing arguments and their relationships as abstract e
162,SJgVU0EKwS,Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations,Yichi Zhang; Ritchie Zhao; Weizhe Hua; Nayun Xu; G. Edward Suh,2020,ICLR 2020,main,Poster,,deep learning;neural network;dynamic quantization;dual precision;efficient gating,0,15.082,0.000,,https://openreview.net/forum?id=SJgVU0EKwS,,offline_iclr,"We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization technique for deep neural networks.","We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization technique for deep neural networks.  PG computes most features in a low precision and only a small proportion of important features in a higher precision to preserve accuracy.  The proposed approach is appl"
163,gVtk4lzhcl,Multi-View Oriented GPLVM: Expressiveness and Efficiency,Zi yang; Ying Li; Zhidi Lin; Michael Minyi Zhang; Pablo M. Olmos,2025,NIPS 2025,main,Poster,probabilistic_methods,Multi-view representation learning;Kernel learning;Random Fourier feature,0,15.057,0.000,,https://openreview.net/forum?id=gVtk4lzhcl,,offline_nips,,"The multi-view Gaussian process latent variable model (MV-GPLVM) aims to learn a unified representation from multi-view data but is hindered by challenges such as limited kernel expressiveness and low computational efficiency. To overcome these issues, we first introduce a new duality between the sp"
164,vzItLaEoDa,Open-World Reinforcement Learning over Long Short-Term Imagination,Jiajian Li; Qi Wang; Yunbo Wang; Xin Jin; Yang Li,2025,ICLR 2025,main,Oral,reinforcement learning,World models;reinforcement learning;visual control,0,14.953,0.000,,https://iclr.cc/virtual/2025/poster/27879,https://openreview.net/pdf?id=vzItLaEoDa,offline_iclr,,"Training visual reinforcement learning agents in a high-dimensional open world presents significant challenges. While various model-based methods have improved sample efficiency by learning interactive world models, these agents tend to be “short-sighted”, as they are typically trained on short snip"
165,faxcxKINBC,Sparse Imagination for Efficient Visual World Model Planning,,2026,ICLR 2026,main,Active,"applications to robotics, autonomy, planning",World Model;Planning;Computational Efficiency;Model Predictive Control;Vision Transformer,0,14.669,0.000,,https://openreview.net/forum?id=faxcxKINBC,,offline_iclr,,"World model based planning has significantly improved decision-making in complex environments by enabling agents to simulate future states and make informed choices.
This computational burden is particularly restrictive in robotics, where resources are severely constrained.
To address this limitatio"
166,jpiSagi8aV,RLVR-World: Training World Models with Reinforcement Learning,Jialong Wu; Shaofeng Yin; Ningya Feng; Mingsheng Long,2025,NIPS 2025,main,Poster,deep_learning,world models;reinforcement learning with verifiable rewards,0,14.299,0.000,,https://openreview.net/forum?id=jpiSagi8aV,,offline_nips,,"World models predict state transitions in response to actions and are increasingly developed across diverse modalities. However, standard training objectives such as maximum likelihood estimation (MLE) often misalign with task-specific goals of world models, i.e., transition prediction metrics like "
167,4E0lCxBD0U,Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models,Yang Zhang; Chenjia Bai; Bin Zhao; Junchi Yan; Xiu Li,2025,ICLR 2025,main,Reject,reinforcement learning,multi-agent reinforcement learning;world models;learning in imagination,0,14.235,0.000,,https://openreview.net/forum?id=4E0lCxBD0U,,offline_iclr,,"Learning a world model for model-free Reinforcement Learning (RL) agents can significantly improve the sample efficiency by learning policies in imagination. However, building a world model for Multi-Agent RL (MARL) can be particularly challenging due to the scalability issue in a centralized archit"
168,2477,Differentiable Abstract Interpretation for Provably Robust Neural Networks,Matthew Mirman; Timon Gehr; Martin Vechev,2018,ICML 2018,main,Oral,,,0,14.008,0.000,,https://icml.cc/virtual/2018/poster/2477,http://proceedings.mlr.press/v80/mirman18b/mirman18b.pdf,offline_icml,,We introduce a scalable method for training robust neural networks based on abstract interpretation. We present several abstract transformers which balance efficiency with precision and show these can be used to train large neural networks that are certifiably robust to adversarial perturbations.
169,YT_hOa02tqO,EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization,Ondrej Bohdal; Yongxin Yang; Timothy Hospedales,2021,NIPS 2021,main,Poster,,Meta-learning;Hyperparameter optimization;Evolution,0,13.971,0.000,,https://nips.cc/virtual/2021/poster/26684,https://openreview.net/pdf?id=YT_hOa02tqO,offline_nips,Efficient gradient-based meta-learning and hyperparameter optimization inspired by evolutionary methods,"Gradient-based meta-learning and hyperparameter optimization have seen significant progress recently, enabling practical end-to-end training of neural networks together with many hyperparameters. Nevertheless, existing approaches are relatively expensive as they need to compute second-order derivati"
170,YK9G4Htdew,Learning Transformer-based World Models with Contrastive Predictive Coding,Maxime Burchi; Radu Timofte,2025,ICLR 2025,main,Spotlight,reinforcement learning,model-based reinforcement learning;transformer network;contrastive predictive coding,0,13.919,0.000,,https://iclr.cc/virtual/2025/poster/29267,https://openreview.net/pdf?id=YK9G4Htdew,offline_iclr,,The DreamerV3 algorithm recently obtained remarkable performance across diverse environment domains by learning an accurate world model based on Recurrent Neural Networks (RNNs). Following the success of model-based reinforcement learning algorithms and the rapid adoption of the Transformer architec
171,b2D9PBNNQ2,IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers,Zhanpeng Zeng; Karthikeyan Sankaralingam; Vikas Singh,2024,ICML 2024,main,Poster,,,0,13.887,0.000,,https://icml.cc/virtual/2024/poster/33657,https://openreview.net/pdf?id=b2D9PBNNQ2,offline_icml,,"GEneral Matrix Multiply (GEMM) is a central operation in deep learning and corresponds to a large chunk of the compute footprint. Therefore, improving its efficiency is an active topic of research. A popular strategy is the use of low bit-width integers to approximate the original matrix entries. Th"
172,aVK4JFpegy,Evaluating the World Model Implicit in a Generative Model,Keyon Vafa; Justin Y. Chen; Ashesh Rambachan; Jon Kleinberg; Sendhil Mullainathan,2024,NIPS 2024,main,Spotlight,evaluation,world models;large language models;evaluation,0,13.839,0.000,,https://neurips.cc/virtual/2024/poster/94550,https://openreview.net/pdf?id=aVK4JFpegy,offline_nips,,Recent work suggests that large language models may implicitly learn world models. How should we assess this possibility? We formalize this question for the case where the underlying reality is governed by a deterministic finite automaton. This includes problems as diverse as simple logical reasonin
173,6556,Planning to Explore via Self-Supervised World Models,Ramanan Sekar; Oleh Rybkin; Kostas Daniilidis; Pieter Abbeel; Danijar Hafner,2020,ICML 2020,main,Poster,,,0,13.805,0.000,,https://icml.cc/virtual/2020/poster/6556,http://proceedings.mlr.press/v119/sekar20a/sekar20a.pdf,offline_icml,,"Reinforcement learning allows solving complex tasks, however, the learning tends to be task-specific and the sample efficiency remains a challenge. We present Plan2Explore, a self-supervised reinforcement learning agent that tackles both these challenges through a new approach to self-supervised exp"
174,tS3gexmfeT,Fusion Token: Enhancing Compression and Efficiency in Language Model Tokenization,Robert Kwiatkowski; Zijian Wang; Robert Giaquinto; Varun Kumar; Xiaofei Ma,2024,ICLR 2024,main,Reject,generative models,tokenizer;large language models;compression,0,13.728,0.000,,https://openreview.net/forum?id=tS3gexmfeT,,offline_iclr,,"In the realm of language models, data encoding is pivotal, influencing efficiency and effectiveness of model training. Byte Pair Encoding (BPE) is a well-established subword tokenization technique that balances computational efficiency and linguistic expressiveness by merging frequent byte or charac"
175,xj0DXLQZCS,World Models as Reference Trajectories for Rapid Motor Adaptation,Carlos Stein Brito; Daniel C McNamee,2025,NIPS 2025,main,Poster,reinforcement_learning,Motor Adaptation;Model-based RL;Rapid Adaptation;Model Reference Control;Data Efficiency;Naturalistic Motor Control,0,13.719,0.000,,https://openreview.net/forum?id=xj0DXLQZCS,,offline_nips,,"Learned control policies often fail when deployed in real-world environments with changing dynamics. When system dynamics shift unexpectedly, performance degrades until models are retrained on new data. We introduce Reflexive World Models (RWM), a dual control framework that uses world model predict"
176,29p13QihRM,Language-Guided Object-Centric World Models for Predictive Control,Youngjoon Jeong; Junha Chun; Soonwoo Cha; Taesup Kim,2025,ICLR 2025,main,Reject,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",Object-Centric Representation;World Model;Predictive Control,0,13.666,0.000,,https://openreview.net/forum?id=29p13QihRM,,offline_iclr,,"A world model is essential for an agent to predict the future and plan in domains such as autonomous driving and robotics. To achieve this, recent advancements have focused on video generation, which has gained significant attention due to the impressive success of diffusion models. However, these m"
177,HbV5vRJMOY,Mixture of Nested Experts: Adaptive Processing of Visual Tokens,Gagan Jain; Nidhi Hegde; Aditya Kusupati; Arsha Nagrani; Shyamal Buch,2024,NIPS 2024,main,Poster,machine_vision,Mixture of Experts;Matryoshka Representation Learning;Information Compression;Efficient Inference,0,13.656,0.000,,https://neurips.cc/virtual/2024/poster/95822,https://openreview.net/pdf?id=HbV5vRJMOY,offline_nips,,"The visual medium (images and videos) naturally contains a large amount of information redundancy, thereby providing a great opportunity for leveraging efficiency in processing. While Vision Transformer (ViT) based models scale effectively to large data regimes, they fail to capitalize on this inher"
178,33120,Scaling Vision Pre-Training to 4K Resolution,Baifeng Shi; Boyi Li; Han Cai; Yao Lu; Sifei Liu,2025,CVPR 2025,main,Highlight,,,0,13.645,0.000,,https://cvpr.thecvf.com/virtual/2025/poster/33120,https://openaccess.thecvf.com/content/CVPR2025/papers/Shi_Scaling_Vision_Pre-Training_to_4K_Resolution_CVPR_2025_paper.pdf,offline_cvpr,,"High-resolution perception of visual details is crucial for daily tasks. Current vision pre-training, however, is still limited to low resolutions (e.g., 378 x 378 pixels) due to the quadratic cost of processing larger images. We introduce PS3 that scales CLIP-style vision pre-training to 4K resolut"
179,WbNf4npMlJ,AdaReP: Plug-and-Play Acceleration for World Model Predictive Control using Adaptive Re-Planning,,2026,ICLR 2026,main,Active,"applications to robotics, autonomy, planning",model predicative control;world model;robot manipulation,0,13.621,0.000,,https://openreview.net/forum?id=WbNf4npMlJ,,offline_iclr,,"We investigate the integration of model predictive control (MPC) with world models for robotic control tasks. Existing MPC solvers often replan at every step or after very few steps, primarily to mitigate the accumulation of world model prediction errors. However, such frequent replanning incurs sub"
180,qjIq4JWFVs,VIRTUAL CELLS AS CAUSAL WORLD MODELS: A PERSPECTIVE ON EVALUATION,Tiffany Callahan; Zane Beckwith; Thomas Merth; Constantijn van der Poel; Pablo Lemos,2026,ICLR 2026,main,Withdraw,"applications to physical sciences (physics, chemistry, biology, etc.)",AI virtual cells;causal world models;causal evaluation;intervention validity;counterfactual consistency;trajectory faithfulness;mechanistic alignment;causal benchmarks;perturbation datasets;evaluation metrics;predictive accuracy vs causality;model reliability;biological simulation;taxonomy of causal metrics;trustworthy AI in biology,0,13.473,0.000,,https://openreview.net/forum?id=qjIq4JWFVs,,offline_iclr,,"This perspective argues that evaluating AI virtual cells requires moving beyond predictive accuracy toward assessing their ability to function as causal world models of biology. Existing benchmarks emphasize fit to observed data, rewarding pattern matching but failing to test responses to interventi"
181,Obefq4k8iG,Horizon Imagination: Efficient On-Policy Training in Diffusion World Models,,2026,ICLR 2026,main,Active,reinforcement learning,world models;diffusion;model-basedreinforcement learning,0,13.463,0.000,,https://openreview.net/forum?id=Obefq4k8iG,,offline_iclr,,"We study diffusion-based world models for reinforcement learning, which offer high generative fidelity but face critical efficiency challenges in control. 
Current methods either require heavyweight models at inference or rely on highly sequential imagination, both of which impose prohibitive comput"
182,CuNHz3zxgm,WorldPack: Compressed Memory Improves Spatial Consistency in Video World Modeling,,2026,ICLR 2026,main,Active,"applications to computer vision, audio, language, and other modalities",world models;memory;video diffusion models,0,13.450,0.000,,https://openreview.net/forum?id=CuNHz3zxgm,,offline_iclr,,"Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations and navigation actions.
Temporally- and spatially-consistent, long-term world modeling has been a long-standing problem, unresolved with even"
183,TG5rvKyEbu,LTD-Bench: Evaluating Large Language Models by Letting Them Draw,Liuhao Lin; Ke Li; Zihan Xu; Yuchen Shi; Yulei Qin,2025,NIPS 2025,Datasets & Benchmarks,Poster,datasets_&_benchmarks_for_language,Large Language Model; Benchmark; Visualization,0,13.443,0.000,,https://openreview.net/forum?id=TG5rvKyEbu,,offline_nips,,Current evaluation paradigms for large language models (LLMs) represent a critical blind spot in AI research—relying on opaque numerical metrics that conceal fundamental limitations in spatial reasoning while providing no intuitive understanding of model capabilities. This deficiency creates a dange
184,OXmRvlihi3,LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning,,2026,ICLR 2026,main,Active,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",Large Language Models;Low-Rank Representation;Efficient Fine-tuning,0,13.421,0.000,,https://openreview.net/forum?id=OXmRvlihi3,,offline_iclr,,"Fine-tuning large language models (LLMs) is crucial for improving their performance on downstream tasks, but full-parameter fine-tuning (Full-FT) is computationally expensive and memory-intensive. Parameter-efficient fine-tuning (PEFT) methods, such as Low-Rank Adaptation (LoRA), address this by opt"
185,Qz7BfmWizk,The motion planning neural circuit in goal-directed navigation as Lie group operator search,Junfeng Zuo; Ying Nian Wu; Si Wu; Wenhao Zhang,2024,NIPS 2024,main,Poster,neuroscience_and_cognitive_science,Lie group equivariance;motion planning;goal-directed navigation;ring attractor network,0,13.400,0.000,,https://neurips.cc/virtual/2024/poster/95206,https://openreview.net/pdf?id=Qz7BfmWizk,offline_nips,,"The information processing in the brain and embodied agents form a sensory-action loop to interact with the world. An important step in the loop is motion planning which selects motor actions based on the current world state and task need. In goal-directed navigation, the brain chooses and generates"
186,skJLOae8ew,From Abstract Noise to Architectural Form: Designing Diffusion Models for Efficient Floor Plan Generation,Santiago Yeomans; Hod Lipson,2025,ICLR 2025,main,Reject,generative models,Architectural Design Automation;Generative Models;Diffusion Models,0,13.397,0.000,,https://openreview.net/forum?id=skJLOae8ew,,offline_iclr,,"In contemporary architectural design, the generation of innovative and efficient floor plans remains a critical challenge. This research introduces a novel application of diffusion models, specifically adapted for the generation of architectural floor plans. Unlike traditional generative models that"
187,7MYu2xO4pp,Gradient-based inference of abstract task representations for generalization in neural networks,Ali Hummos; Felipe del Rio; Mien Brabeeba Wang; Julio Hurtado; Cristian Buc Calderon,2025,ICLR 2025,main,Reject,"transfer learning, meta learning, and lifelong learning",Cognitive science;cognitive control;cognitive abstractions;task representations;context-dependent models;variational expectation-maximization,0,13.259,0.000,,https://openreview.net/forum?id=7MYu2xO4pp,,offline_iclr,,Humans and many animals show remarkably adaptive behavior and can respond differently to the same input depending on their internal goals. The brain not only represents the intermediate abstractions needed to perform a computation but also actively maintains a representation of the computation itsel
188,92AFW5nq8M,RESOLVE: Relational Reasoning with Symbolic and Object-Level Features Using Vector Symbolic Processing,Mohamed Mejri; Chandramouli Amarnath; Abhijit Chatterjee,2025,ICLR 2025,main,Withdraw,"neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)",Abstract Reasoning;Neuro Vector Symbolic Architectures;Self-Attention,0,13.204,0.000,,https://openreview.net/forum?id=92AFW5nq8M,,offline_iclr,,"Modern transformer-based encoder-decoder architectures struggle with reasoning tasks due to their inability to effectively extract relational information between input objects (data/tokens). Recent work introduced the $\textit{Abstractor}$ module, embedded between transformer layers, to address this"
189,b907d5dcfd,"Neurobiology, Psychophysics, and Computational Models of Visual Attention",Ernst Niebur; Bruno A. Olshausen,1993,NIPS 1993,main,Poster,,,0,13.173,0.000,,https://papers.nips.cc/paper_files/paper/1993/hash/ce78d1da254c0843eb23951ae077ff5f-Abstract.html,https://papers.nips.cc/paper_files/paper/1993/file/ce78d1da254c0843eb23951ae077ff5f-Paper.pdf,offline_nips,,Abstract Unavailable
190,FbjQYJKAyt,Implicit Neural Representation Image Codec with Mixed Context for Fast Decoding,Xiang Liu; Jiahong Chen; Bin Chen; Zimo Liu; Shu-Tao Xia,2024,ICLR 2024,main,Withdraw,"representation learning for computer vision, audio, language, and other modalities",Image Compression;Implicit Neural Representation;Adaptive Entropy Modeling,0,13.164,0.000,,https://openreview.net/forum?id=FbjQYJKAyt,,offline_iclr,,"Image compression using Implicit Neural Representation (INR) is an emerging technology. While it may not match the quality of cutting-edge autoencoder models, it offers two key benefits: low computational complexity and parameter-free decoding. It also surpasses many traditional and early neural com"
191,iq2FBcjYRn,SlowFormer: Universal Adversarial Patch for Attack on Compute and Energy Efficiency of Inference Efficient Vision Transformers,Navaneet K L; Soroush Abbasi Koohpayegani; Essam Sleiman; Hamed Pirsiavash,2024,ICLR 2024,main,Withdraw,"general machine learning (i.e., none of the above)",Adversarial attack;Efficient Transformers;Energy Attack;Transformers;Universal Adversarial Patch,0,13.115,0.000,,https://openreview.net/forum?id=iq2FBcjYRn,,offline_iclr,,"Recently, there has been a lot of progress in reducing the computation of deep models at inference time. These methods can reduce both the computational needs and power usage of deep models. Some of these approaches adaptively scale the compute based on the input instance. We show that such models c"
192,1RE0H6mU7M,MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning,Zohar Rimon; Tom Jurgenson; Orr Krupnik; Gilad Adler; Aviv Tamar,2024,ICLR 2024,main,Poster,reinforcement learning,Meta Reinforcement Learning;World Models;Model Based Reinforcement Learning,0,13.040,0.000,,https://iclr.cc/virtual/2024/poster/19589,https://openreview.net/pdf?id=1RE0H6mU7M,offline_iclr,,"Meta-reinforcement learning (meta-RL) is a promising framework for tackling challenging domains requiring efficient exploration. Existing meta-RL algorithms are characterized by low sample efficiency, and mostly focus on low-dimensional task distributions. In parallel, model-based RL methods have be"
193,MKDdTASg_1y,A Benchmark for Compositional Visual Reasoning,Aimen Zerroug; Mohit Vaishnav; Julien Colin; Sebastian Musslick; Thomas Serre,2022,NIPS 2022,Datasets & Benchmarks,Accept,,Abstract Visual Reasoning;Compositionality;Data Efficiency;Transfer learning,0,13.009,0.000,,https://nips.cc/virtual/2022/poster/55612,https://openreview.net/pdf?id=MKDdTASg_1y,offline_nips,A visual reasoning benchmark that incorporates a large number of novel relations and focuses on evaluating compositionality and sample efficiency.,A fundamental component of human vision is our ability to parse complex visual scenes and judge the relations between their constituent objects. AI benchmarks for visual reasoning have driven rapid progress in recent years with state-of-the-art systems now reaching human accuracy on some of these be
194,eJhgguibXu,Using Approximate Models for Efficient Exploration in Reinforcement Learning,Divanisha Patel; Benjamin Rosman; Steven James,2024,ICLR 2024,main,Reject,reinforcement learning,Model-based reinforcement learning;graph neural networks;intuitive physics;exploration,0,12.998,0.000,,https://openreview.net/forum?id=eJhgguibXu,,offline_iclr,,"In model-based reinforcement learning, an agent uses a learned model of environment dynamics to improve a policy. Using a learned model of the environment to select actions has many benefits. It can be used to generate experience for learning a policy or simulate potential outcomes in planning. It a"
195,OrgL5DsU0f,DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving,,2026,ICLR 2026,main,Active,datasets and benchmarks,Benchmark;Autonomous Driving;Generative World Model,0,12.986,0.000,,https://openreview.net/forum?id=OrgL5DsU0f,,offline_iclr,,"Video generation models, as one form of world models, has emerged as one of the most exciting frontiers in AI, promising agents the ability to imagine the future by modeling the temporal evolution of complex scenes. 
In autonomous driving, this vision gives rise to driving world models—generative si"
196,4X9RpKH4Ls,Can Transformers Do Enumerative Geometry?,Baran Hashemi; Roderic Guigo Corominas; Alessandro Giacchetto,2025,ICLR 2025,main,Poster,"applications to physical sciences (physics, chemistry, biology, etc.)",AI for Mathematics;Algebraic Geometry;Theorem Discovery;Transformers;Recursive functions;Interpretability Analysis and world model.,0,12.965,0.000,,https://iclr.cc/virtual/2025/poster/31007,https://openreview.net/pdf?id=4X9RpKH4Ls,offline_iclr,,"We introduce a Transformer-based approach to computational enumerative geometry, specifically targeting the computation of $\psi$-class intersection numbers on the moduli space of curves. Traditional methods for calculating these numbers suffer from factorial computational complexity, making them im"
197,3Cr6C2zNKw,Uncovering Untapped Potential in Sample-Efficient World Model Agents,Lior Cohen; Kaixin Wang; Bingyi Kang; Uri Gadot; Shie Mannor,2025,NIPS 2025,main,Reject,reinforcement_learning,world models;deep reinforcement learning;intrinsic motivation;sample efficiency,0,12.932,0.000,,https://openreview.net/forum?id=3Cr6C2zNKw,,offline_nips,,"World model (WM) agents enable sample-efficient reinforcement learning by learning policies entirely from simulated experience.
However, existing token-based world models (TBWMs) are limited to visual inputs and discrete actions, restricting their adoption and applicability. Moreover, although both "
198,STUGfUz8ob,When can transformers reason with abstract symbols?,Enric Boix-Adserà; Omid Saremi; Emmanuel Abbe; Samy Bengio; Etai Littwin,2024,ICLR 2024,main,Poster,learning theory,transformers;language models;reasoning;theoretical analysis;variable binding,0,12.901,0.000,,https://iclr.cc/virtual/2024/poster/18602,https://openreview.net/pdf?id=STUGfUz8ob,offline_iclr,,"We investigate the capabilities of transformer models on relational reasoning tasks. In these tasks, models are trained on a set of strings encoding abstract relations, and are then tested out-of-distribution on data that contains symbols that did not appear in the training dataset. We prove that fo"
199,6912,Generating Images with Perceptual Similarity Metrics based on Deep Networks,Alexey Dosovitskiy; Thomas Brox,2016,NIPS 2016,main,Poster,,,0,12.853,0.000,,https://nips.cc/virtual/2016/poster/6912,https://papers.nips.cc/paper_files/paper/2016/file/371bce7dc83817b7893bcdeed13799b5-Paper.pdf,offline_nips,,"We propose a class of loss functions, which we call deep perceptual similarity metrics (DeePSiM), allowing to generate sharp high resolution images from compressed abstract representations. Instead of computing distances in the image space, we compute distances between image features extracted by de"
200,LGvlCcMgWqb,Temporally Abstract Partial Models,Khimya Khetarpal; Zafarali Ahmed; Gheorghe Comanici; Doina Precup,2021,NIPS 2021,main,Poster,,reinforcement learning;model-based reinforcement learning;temporal abstraction;options;partial models;affordances,0,12.640,0.000,,https://nips.cc/virtual/2021/poster/26609,https://openreview.net/pdf?id=LGvlCcMgWqb,offline_nips,"TLDR: We propose temporally abstract partial options models via the notion of affordances, with theoretical guarantees and empirical analysis demonstrating improvement in final performance and sample efficiency.","Humans and animals have the ability to reason and make predictions about different courses of action at many time scales. In reinforcement learning, option models (Sutton, Precup \& Singh, 1999; Precup, 2000) provide the framework for this kind of temporally abstract prediction and reasoning. Natura"
201,jnps5YwNlU,Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling,Yuanbang Liang; Jing Wu; Yu-Kun Lai; Yipeng Qin,2024,ICML 2024,main,Spotlight,,,0,12.571,0.000,,https://icml.cc/virtual/2024/poster/33287,https://openreview.net/pdf?id=jnps5YwNlU,offline_icml,,"Despite impressive results, deep generative models require massive datasets for training, and as dataset size increases, effective evaluation metrics like precision and recall (P&R) become computationally infeasible on commodity hardware. In this paper, we address this challenge by proposing efficie"
202,PK07eretkF,DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge,Wenyao Zhang; Hongsi Liu; Zekun Qi; Yunnan Wang; XinQiang Yu,2025,NIPS 2025,main,Poster,other,Vision language action models;comprehensive knowledge forecasting;robot learning,0,12.521,0.000,,https://openreview.net/forum?id=PK07eretkF,,offline_nips,,"Recent advances in vision-language-action (VLA) models have shown promise in integrating image generation with action prediction to improve generalization and reasoning in robot manipulation. However, existing methods are limited to challenging image-based forecasting, which suffers from redundant i"
203,ASPC2Ut0CB,Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models,,2026,ICLR 2026,main,Active,"applications to physical sciences (physics, chemistry, biology, etc.)",World Model;Spatio-temporal data mining,0,12.478,0.000,,https://openreview.net/forum?id=ASPC2Ut0CB,,offline_iclr,,"Physical spatiotemporal forecasting poses a dual challenge: The inherent stochasticity of physical systems makes it difficult to capture extreme or rare events, especially under \textit{data scarcity}. Moreover, many critical domain-specific metrics are \textit{non-differentiable}, precluding their "
204,RN7RzMxwjC,Harmony World Models: Boosting Sample Efficiency for Model-based Reinforcement Learning,Haoyu Ma; Jialong Wu; Ningya Feng; Jianmin Wang; Mingsheng Long,2024,ICLR 2024,main,Reject,reinforcement learning,model-based reinforcemet learning;world model,0,12.422,0.000,,https://openreview.net/forum?id=RN7RzMxwjC,,offline_iclr,,"Model-based reinforcement learning (MBRL) holds the promise of sample-efficient learning by utilizing a world model, which models how the environment works and typically encompasses components for two tasks: observation modeling and reward modeling. In this paper, through a dedicated empirical inves"
205,1S8ndwxMts,Towards Robust Evaluation of Protein Generative Models: A Systematic Analysis of Metrics,Pavel Strashnov; Andrey Shevtsov; Viacheslav Meshchaninov; Maria Ivanova; Fedor Nikolaev,2025,ICLR 2025,main,Reject,"applications to physical sciences (physics, chemistry, biology, etc.)",evaluation metrics;protein;protein generative models,0,12.388,0.000,,https://openreview.net/forum?id=1S8ndwxMts,,offline_iclr,,"The rapid advancement of protein generative models necessitates robust and principled methods for their evaluation and comparison. As new models of increasing complexity continue to emerge, it is crucial to ensure that the metrics used for assessment are well-understood and reliable. In this work, w"
206,mzLOnTb3WH,WIMLE: Uncertainty‑Aware World Models with IMLE for Sample‑Efficient Continuous Control,,2026,ICLR 2026,main,Active,reinforcement learning,Reinforcement Learning;Model-based RL,0,12.214,0.000,,https://openreview.net/forum?id=mzLOnTb3WH,,offline_iclr,,"Model-based reinforcement learning promises strong sample efficiency but often underperforms in practice due to compounding model error, unimodal world models that average over multi-modal dynamics, and overconfident predictions that bias learning. We introduce WIMLE, a model-based method that exten"
207,17634,BRP-NAS: Prediction-based NAS using GCNs,Lukasz Dudziak; Thomas Chau; Mohamed Abdelfattah; Royson Lee; Hyeji Kim,2020,NIPS 2020,main,Poster,,,0,12.153,0.000,,https://nips.cc/virtual/2020/poster/17634,https://papers.nips.cc/paper_files/paper/2020/file/768e78024aa8fdb9b8fe87be86f64745-Paper.pdf,offline_nips,,"Neural architecture search (NAS) enables researchers to automatically explore broad design spaces in order to improve efficiency of neural networks. This efficiency is especially important in the case of on-device deployment, where improvements in accuracy should be balanced out with computational d"
208,Qyp3Rni2g1,Efficiency Pentathlon: A Standardized Benchmark for Efficiency Evaluation,Hao Peng; Qingqing Cao; Jesse Dodge; Matthew E Peters; Jared Fernandez,2024,ICLR 2024,main,Reject,datasets and benchmarks,Efficiency;evaluation;benchmark;natural language processing,0,12.149,0.000,,https://openreview.net/forum?id=Qyp3Rni2g1,,offline_iclr,,"Rising computational demands of modern natural language processing (NLP) systems have increased the barrier to entry for cutting-edge research while posing serious environmental concerns. Yet, progress on model efficiency has been impeded by practical challenges in model evaluation and comparison. F"
209,db72591e4b,A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural Networks,Alexander Singer; John P. Donoghue,1987,NIPS 1987,main,Poster,,,0,12.095,0.000,,https://papers.nips.cc/paper_files/paper/1987/hash/71996f80223a3e89a5bd0139908097db-Abstract.html,https://papers.nips.cc/paper_files/paper/1987/file/71996f80223a3e89a5bd0139908097db-Paper.pdf,offline_nips,,Abstract Unavailable
210,,SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and Time,Zhening Huang; Hyeonho Jeong; Xuelin Chen; Yulia Gryaditskaya; Tuanfeng Y. Wang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25075v1,https://arxiv.org/pdf/2512.25075v1,arxiv,,"We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-rendering the scene for continuous"
211,,Randomization Times under Quantum Chaotic Hamiltonian Evolution,Souradeep Ghosh; Nicholas Hunter-Jones; Joaquin F. Rodriguez-Nieva,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25074v1,https://arxiv.org/pdf/2512.25074v1,arxiv,,"Randomness generation through quantum-chaotic evolution underpins foundational questions in statistical mechanics and applications across quantum information science, including benchmarking, tomography, metrology, and demonstrations of quantum computational advantage. While statistical mechanics suc"
212,,Edit3r: Instant 3D Scene Editing from Sparse Unposed Images,Jiageng Liu; Weijie Lyu; Xueting Li; Yejie Guo; Ming-Hsuan Yang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25071v1,https://arxiv.org/pdf/2512.25071v1,arxiv,,"We present Edit3r, a feed-forward framework that reconstructs and edits 3D scenes in a single pass from unposed, view-inconsistent, instruction-edited images. Unlike prior methods requiring per-scene optimization, Edit3r directly predicts instruction-aligned 3D edits, enabling fast and photorealisti"
213,,Coordinated Humanoid Manipulation with Choice Policies,Haozhi Qi; Yen-Jen Wang; Toru Lin; Brent Yi; Yi Ma,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25072v1,https://arxiv.org/pdf/2512.25072v1,arxiv,,"Humanoid robots hold great promise for operating in human-centric environments, yet achieving robust whole-body coordination across the head, hands, and legs remains a major challenge. We present a system that combines a modular teleoperation interface with a scalable learning framework to address t"
214,,Scaling Open-Ended Reasoning to Predict the Future,Nikhil Chandak; Shashwat Goel; Ameya Prabhu; Moritz Hardt; Jonas Geiping,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25070v1,https://arxiv.org/pdf/2512.25070v1,arxiv,,"High-stakes decision making involves reasoning under uncertainty about the future. In this work, we train language models to make predictions on open-ended forecasting questions. To scale up training data, we synthesize novel forecasting questions from global events reported in daily news, using a f"
215,,FineTec: Fine-Grained Action Recognition Under Temporal Corruption via Skeleton Decomposition and Sequence Completion,Dian Shao; Mingfei Shi; Like Liu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25067v1,https://arxiv.org/pdf/2512.25067v1,arxiv,,"Recognizing fine-grained actions from temporally corrupted skeleton sequences remains a significant challenge, particularly in real-world scenarios where online pose estimation often yields substantial missing data. Existing methods often struggle to accurately recover temporal dynamics and fine-gra"
216,,From Inpainting to Editing: A Self-Bootstrapping Framework for Context-Rich Visual Dubbing,Xu He; Haoxian Zhang; Hejia Chen; Changyuan Zheng; Liyang Chen,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25066v1,https://arxiv.org/pdf/2512.25066v1,arxiv,,"Audio-driven visual dubbing aims to synchronize a video's lip movements with new speech, but is fundamentally challenged by the lack of ideal training data: paired videos where only a subject's lip movements differ while all other visual conditions are identical. Existing methods circumvent this wit"
217,,Vulcan: Instance-Optimal Systems Heuristics Through LLM-Driven Search,Rohit Dwivedula; Divyanshu Saxena; Sujay Yadalam; Daehyeok Kim; Aditya Akella,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25065v1,https://arxiv.org/pdf/2512.25065v1,arxiv,,"Resource-management tasks in modern operating and distributed systems continue to rely primarily on hand-designed heuristics for tasks such as scheduling, caching, or active queue management. Designing performant heuristics is an expensive, time-consuming process that we are forced to continuously g"
218,,Feeling Blue: Constructing a Robust SALT3 UV Template and Constraining its Redshift Dependency,Qinan Wang; David O. Jones; Justin D. R. Pierel; Matthew R. Siebert; W. D'Arcy Kenworthy,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25064v1,https://arxiv.org/pdf/2512.25064v1,arxiv,,"Upcoming cosmological surveys will obtain numerous rest-frame ultraviolet (UV) observations of Type Ia supernovae (SNe Ia), yet there is concern about how standardizable SNe Ia are in the UV. In this work, we train a robust optical--UV SED model for SNe Ia (SALT3-UV) with the open-source model-train"
219,,Many Minds from One Model: Bayesian Transformers for Population Intelligence,Diji Yang; Yi Zhang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25063v1,https://arxiv.org/pdf/2512.25063v1,arxiv,,"Despite their scale and success, modern transformers are almost universally trained as single-minded systems: optimization produces one deterministic set of parameters, representing a single functional hypothesis about the data. Motivated by the idea that intelligence emerge from many minds, we prop"
220,,On the geometry and topology of representations: the manifolds of modular addition,Gabriela Moisescu-Pareja; Gavin McCracken; Harley Wiltzer; Vincent Létourneau; Colin Daniels,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25060v1,https://arxiv.org/pdf/2512.25060v1,arxiv,,"The Clock and Pizza interpretations, associated with architectures differing in either uniform or learnable attention, were introduced to argue that different architectural designs can yield distinct circuits for modular addition. In this work, we show that this is not the case, and that both unifor"
221,,Reliable and Resilient Collective Communication Library for LLM Training and Serving,Wei Wang; Nengneng Yu; Sixian Xiong; Zaoxing Liu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25059v1,https://arxiv.org/pdf/2512.25059v1,arxiv,,"Modern ML training and inference now span tens to tens of thousands of GPUs, where network faults can waste 10--15\% of GPU hours due to slow recovery. Common network errors and link fluctuations trigger timeouts that often terminate entire jobs, forcing expensive checkpoint rollback during training"
222,,Sequential Bayesian parameter-state estimation in dynamical systems with noisy and incomplete observations via a variational framework,Liliang Wang; Alex Gorodetsky,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25056v1,https://arxiv.org/pdf/2512.25056v1,arxiv,,"Online joint estimation of unknown parameters and states in a dynamical system with uncertainty quantification is crucial in many applications. For example, digital twins dynamically update their knowledge of model parameters and states to support prediction and decision-making. Reliability and comp"
223,,Context-aware LLM-based AI Agents for Human-centered Energy Management Systems in Smart Buildings,Tianzhi He; Farrokh Jazizadeh,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25055v1,https://arxiv.org/pdf/2512.25055v1,arxiv,,This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy management in smart buildings through natural language interaction. The proposed framework comprises three 
224,,Fluid dynamics as intersection problem,Nikita Nekrasov; Paul Wiegmann,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25053v1,https://arxiv.org/pdf/2512.25053v1,arxiv,,"We formulate the covariant hydrodynamics equations describing the fluid dynamics as the problem of intersection theory on the infinite dimensional symplectic manifold associated with spacetime. This point of view separates the structures related to the equation of state, the geometry of spacetime, a"
225,,The PDE-ODI principle and cylindrical mean curvature flows,Richard H. Bamler; Yi Lai,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25050v1,https://arxiv.org/pdf/2512.25050v1,arxiv,,"We introduce a new approach for analyzing ancient solutions and singularities of mean curvature flow that are locally modeled on a cylinder. Its key ingredient is a general mechanism, called the \emph{PDE--ODI principle}, which converts a broad class of parabolic differential equations into systems "
226,,Extreme nonlinear optics in optical fibers,Mario Ferraro; Bertrand Kibler; Pierre Béjot; Frédéric Gérome; Benoit Debord,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25046v1,https://arxiv.org/pdf/2512.25046v1,arxiv,,"This paper reviews the field of extreme nonlinear optics in optical fibers, highlighting key phenomena and advancements. It discusses multiple ionization effects caused by femtosecond laser pulses that generate plasma and induce permanent material modifications, as well as plasma luminescence and it"
227,,Bayesian Elastic Net Regression with Structured Prior Dependence,Christopher M. Hans; Ningyi Liu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25045v1,https://arxiv.org/pdf/2512.25045v1,arxiv,,"Many regularization priors for Bayesian regression assume the regression coefficients are a priori independent. In particular this is the case for standard Bayesian treatments of the lasso and the elastic net. While independence may be reasonable in some data-analytic settings, incorporating depende"
228,,Compound Estimation for Binomials,Yan Chen; Lihua Lei,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25042v1,https://arxiv.org/pdf/2512.25042v1,arxiv,,"Many applications involve estimating the mean of multiple binomial outcomes as a common problem -- assessing intergenerational mobility of census tracts, estimating prevalence of infectious diseases across countries, and measuring click-through rates for different demographic groups. The most standa"
229,,Towards precision cosmology with Voids x CMB correlations (I): Roman-Agora mock catalogs and pipeline validation,Mar Pérez Sar; Carlos Hernández Monteagudo; András Kovács; Alice Pisani,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25040v1,https://arxiv.org/pdf/2512.25040v1,arxiv,,"We construct and validate a set of multi-purpose mock galaxy catalogs designed to capture, to different degrees of accuracy, the main characteristics of the Nancy Grace Roman Space Telescope survey. These catalogs provide a foundation for void statistics and various CMB cross-correlation analyses. O"
230,,The Hochschild homology of a noncommutative symmetric quotient stack,Rina Anno; Vladimir Baranovsky; Timothy Logvinenko,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25039v1,https://arxiv.org/pdf/2512.25039v1,arxiv,,"We prove an orbifold type decomposition theorem for the Hochschild homology of the symmetric powers of a small DG category $\mathcal{A}$. In noncommutative geometry, these can be viewed as the noncommutative symmetric quotient stacks of $\mathcal{A}$. We use this decomposition to show that the total"
231,,Anomalous (3+1)d Fermionic Topological Quantum Field Theories via Symmetry Extension,Zheyan Wan; Juven Wang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25038v1,https://arxiv.org/pdf/2512.25038v1,arxiv,,"Discrete finite-group global symmetries may suffer from nonperturbative 't-Hooft anomalies. Such global anomalies can be canceled by anomalous symmetry-preserving topological quantum field theories (TQFTs), which contain no local point operators but only extended excitations such as line and surface"
232,,Large Neutrino-Dark Matter Interactions: From Effective Field Theory to Ultraviolet Completions,K. S. Babu; P. S. Bhupal Dev; Anil Thapa,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25035v1,https://arxiv.org/pdf/2512.25035v1,arxiv,,"We develop a general effective field theory (EFT) framework for neutrino-dark matter (DM) interactions, and apply it to systematically find all possible gauge-invariant ultraviolet (UV) completions at a given EFT operator dimension. Our goal here is to find simple UV-complete models that can realize"
233,,Generative Classifiers Avoid Shortcut Solutions,Alexander C. Li; Ananya Kumar; Deepak Pathak,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25034v1,https://arxiv.org/pdf/2512.25034v1,arxiv,,"Discriminative approaches to classification often learn shortcuts that hold in-distribution but fail even under minor distribution shift. This failure mode stems from an overreliance on features that are spuriously correlated with the label. We show that generative classifiers, which use class-condi"
234,,EF(X) Orientations: A Parameterized Complexity Perspective,Sotiris Kanellopoulos; Edouard Nemery; Christos Pergaminelis; Minas Marios Sotiriou; Manolis Vasilakis,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25033v1,https://arxiv.org/pdf/2512.25033v1,arxiv,,"The concept of fair orientations in graphs was introduced by Christodoulou, Fiat, Koutsoupias, and Sgouritsa in 2023, naturally modeling fair division scenarios in which resources are only contested by neighbors. In this model, vertices represent agents and undirected edges represent goods; edges ha"
235,,Fractal conduction pathways governing ionic transport in a glass,J. L. Iguain; F. O. Sanchez-Varreti; M. A. Frechero,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25031v1,https://arxiv.org/pdf/2512.25031v1,arxiv,,"We present a systematic characterization of the fractal conduction pathways governing ionic transport in a non-crystalline solid below the glass-transition temperature. Using classical molecular dynamics simulations of lithium metasilicate, we combine mobility-resolved dynamical analysis with a real"
236,,Multivariate Generalized Counting Process via Gamma Subordination,Manisha Dhillon; Kuldeep Kumar Kataria; Shyan Ghosh,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25030v1,https://arxiv.org/pdf/2512.25030v1,arxiv,,"In this paper, we study a multivariate gamma subordinator whose components are independent gamma processes subject to a random time governed by an independent negative binomial process. We derive the explicit expressions for its joint Laplace-Stieltjes transform, its probability density function and"
237,,Mod $p$ Poincaré duality for $p$-adic period domains,Guillaume Pignon-Ywanne,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25029v1,https://arxiv.org/pdf/2512.25029v1,arxiv,,"In this article, we introduce a new class of smooth partially proper rigid analytic varieties over a $p$-adic field that satisfy Poincaré duality for étale cohomology with mod $p$-coefficients : the varieties satisfying ""primitive comparison with compact support"". We show that almost proper varietie"
238,,Universal Seesaw Pati-Salam Model with P for Strong CP,K. S. Babu; Sumit Biswas,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25028v1,https://arxiv.org/pdf/2512.25028v1,arxiv,,"We develop a universal seesaw version of the Pati-Salam model wherein quarks and leptons of each family are unified into common multiplets transforming as $ψ_L(2,1,4))+ ψ_R((1,2,4)$ under the $SU(2)_L \times SU(2)_R \times SU(4)_c$ gauge symmetry. Parity symmetry is spontaneously broken in the model"
239,,Computational Analysis of Disease Progression in Pediatric Pulmonary Arterial Hypertension,Omar Said; Christopher Tossas-Betancourt; Mary K. Olive; Jimmy C. Lu; Adam Dorfman,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25027v1,https://arxiv.org/pdf/2512.25027v1,arxiv,,"Pulmonary arterial hypertension (PAH) is a progressive cardiopulmonary disease that leads to increased pulmonary pressures, vascular remodeling, and eventual right ventricular (RV) failure. Pediatric PAH remains understudied due to limited data and the lack of targeted diagnostic and therapeutic str"
240,,Modeling Language as a Sequence of Thoughts,Nasim Borazjanizadeh; James McClelland,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25026v1,https://arxiv.org/pdf/2512.25026v1,arxiv,,"Transformer language models can generate strikingly natural text by modeling language as a sequence of tokens. Yet, by relying primarily on surface-level co-occurrence statistics, they fail to form globally consistent latent representations of entities and events, lack of which contributes to brittl"
241,,Modewise Additive Factor Model for Matrix Time Series,Elynn Chen; Yuefeng Han; Jiayu Li; Ke Xu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25025v1,https://arxiv.org/pdf/2512.25025v1,arxiv,,"We introduce a Modewise Additive Factor Model (MAFM) for matrix-valued time series that captures row-specific and column-specific latent effects through an additive structure, offering greater flexibility than multiplicative frameworks such as Tucker and CP factor models. In MAFM, each observation d"
242,,ResponseRank: Data-Efficient Reward Modeling through Preference Strength Learning,Timo Kaufmann; Yannick Metz; Daniel Keim; Eyke Hüllermeier,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25023v1,https://arxiv.org/pdf/2512.25023v1,arxiv,,"Binary choices, as often used for reinforcement learning from human feedback (RLHF), convey only the direction of a preference. A person may choose apples over oranges and bananas over grapes, but which preference is stronger? Strength is crucial for decision-making under uncertainty and generalizat"
243,,Real Riemann Surfaces: Smooth and Discrete,Johanna Düntsch; Felix Günther,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25022v1,https://arxiv.org/pdf/2512.25022v1,arxiv,,This paper develops a discrete theory of real Riemann surfaces based on quadrilateral cellular decompositions (quad-graphs) and a linear discretization of the Cauchy-Riemann equations. We construct a discrete analogue of an antiholomorphic involution and classify the topological types of discrete re
244,,"Detector Response Matrices, Effective Areas, and Flash-Effective Areas for Radiation Detectors",Gregory Bowers; Eve Chase; William Ford; Daniel Coupland; Brian Larsen,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25021v1,https://arxiv.org/pdf/2512.25021v1,arxiv,,"A Detector Response Matrix (DRM) is a discrete representation of an instrument's Detector Response Function (DRF), which quantifies how many discrete energy depositions occur in a detector volume for a given distribution of particles incident on the detector. For simple radiation detectors that can "
245,,Loop-Level Lepton Flavor Violation and Diphoton Signals in the Minimal Left-Right Symmetric Model,Shufang Qiang; Peiwen Wu; Yongchao Zhang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25019v1,https://arxiv.org/pdf/2512.25019v1,arxiv,,"The left-right symmetric model (LRSM) could not only restore parity of the weak interaction, but also provide natural explanations of the tiny active neutrino masses via the seesaw mechanisms. The $SU(2)_R$-breaking scalar $H_3$ can induce lepton flavor violating (LFV) effects in the minimal version"
246,,Strengthening Dual Bounds for Multicommodity Capacitated Network Design with Unsplittable Flow Constraints,Lacy M. Greening; Santanu S. Dey; Alan L. Erera,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25018v1,https://arxiv.org/pdf/2512.25018v1,arxiv,,"Multicommodity capacitated network design (MCND) models can be used to optimize the consolidation of shipments within e-commerce fulfillment networks. In practice, fulfillment networks require that shipments with the same origin and destination follow the same transfer path. This unsplittable flow r"
247,,"Approximations for the Weighted Reversal, Transposition, and Indel Distance Problem with Intergenic Region Information",Gabriel Siqueira; Alexsandro Oliveira Alexandrino; Zanoni Dias,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25016v1,https://arxiv.org/pdf/2512.25016v1,arxiv,,"Genome rearrangement distances are an established method in genome comparison. Works in this area may include various rearrangement operations representing large-scale mutations, gene orientation information, the number of nucleotides in intergenic regions, and weights reflecting the expected freque"
248,,MAMA-Memeia! Multi-Aspect Multi-Agent Collaboration for Depressive Symptoms Identification in Memes,Siddhant Agarwal; Adya Dhuler; Polly Ruhnke; Melvin Speisman; Md Shad Akhtar,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25015v1,https://arxiv.org/pdf/2512.25015v1,arxiv,,"Over the past years, memes have evolved from being exclusively a medium of humorous exchanges to one that allows users to express a range of emotions freely and easily. With the ever-growing utilization of memes in expressing depressive sentiments, we conduct a study on identifying depressive sympto"
249,,Diffusion Language Models are Provably Optimal Parallel Samplers,Haozhe Jiang; Nika Haghtalab; Lijie Chen,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25014v1,https://arxiv.org/pdf/2512.25014v1,arxiv,,Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive models for faster inference via parallel token generation. We provide a rigorous foundation for this advantage by formalizing a model of parallel sampling and showing that DLMs augmented with polynomial-length
250,,Parity order as a fundamental driver of bosonic topology,Ashirbad Padhan; Harsh Nigam,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25011v1,https://arxiv.org/pdf/2512.25011v1,arxiv,,"Symmetry-protected topological (SPT) phases in interacting bosonic systems have been extensively studied, yet most realizations rely on fine-tuned interactions or enlarged symmetries. Here we show that a qualitatively different mechanism--parity order coupled to bond dimerization--acts as a fundamen"
251,,Bounding regularity of $\mathrm{VI}^m$-modules,Wee Liang Gan; Khoa Ta,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25010v1,https://arxiv.org/pdf/2512.25010v1,arxiv,,Fix a finite field $\mathbb{F}$. Let $\mathrm{VI}$ be a skeleton of the category of finite dimensional $\mathbb{F}$-vector spaces and injective $\mathbb{F}$-linear maps. We study $\mathrm{VI}^m$-modules over a noetherian commutative ring in the nondescribing characteristic case. We prove that if a f
252,,FoundationSLAM: Unleashing the Power of Depth Foundation Models for End-to-End Dense Visual SLAM,Yuchen Wu; Jiahe Li; Fabio Tosi; Matteo Poggi; Jin Zheng,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25008v1,https://arxiv.org/pdf/2512.25008v1,arxiv,,"We present FoundationSLAM, a learning-based monocular dense SLAM system that addresses the absence of geometric consistency in previous flow-based approaches for accurate and robust tracking and mapping. Our core idea is to bridge flow estimation with geometric reasoning by leveraging the guidance f"
253,,"Distributions of wide binary stars in theory and in Gaia data: III. Orbital momenta, masses, and manifestations of MOND",Valeri V. Makarov,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25002v1,https://arxiv.org/pdf/2512.25002v1,arxiv,,"Using the censored catalog of 103,169 resolved Gaia DR3 binary stars with accurate astrometric data for each component, a new observable, object-specific parameter is computed for each pair: the projected orbital momentum. This parameter is the product of four functions of physical characteristics: "
254,,The local limit of weighted spanning trees on balanced networks,Ágnes Kúsz,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25001v1,https://arxiv.org/pdf/2512.25001v1,arxiv,,"We prove that the local limit of the weighted spanning trees on any simple connected high degree almost regular sequence of electric networks is the Poisson(1) branching process conditioned to survive forever, by generalizing [NP22] and closing a gap in their proof. We also study the local statistic"
255,,Bi-C2R: Bidirectional Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification,Zhenyu Cui; Jiahuan Zhou; Yuxin Peng,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25000v1,https://arxiv.org/pdf/2512.25000v1,arxiv,,"Lifelong person Re-IDentification (L-ReID) exploits sequentially collected data to continuously train and update a ReID model, focusing on the overall performance of all data. Its main challenge is to avoid the catastrophic forgetting problem of old knowledge while training on new data. Existing L-R"
256,,Basic Inequalities for First-Order Optimization with Applications to Statistical Risk Analysis,Seunghoon Paik; Kangjie Zhou; Matus Telgarsky; Ryan J. Tibshirani,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24999v1,https://arxiv.org/pdf/2512.24999v1,arxiv,,"We introduce \textit{basic inequalities} for first-order iterative optimization algorithms, forming a simple and versatile framework that connects implicit and explicit regularization. While related inequalities appear in the literature, we isolate and highlight a specific form and develop it as a w"
257,,Numerical study of boson mixtures with multi-component continuous matrix product states,Wei Tang; Benoît Tuybens; Jutho Haegeman,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24998v1,https://arxiv.org/pdf/2512.24998v1,arxiv,,"The continuous matrix product state (cMPS) ansatz is a promising numerical tool for studying quantum many-body systems in continuous space. Although it provides a clean framework that allows one to directly simulate continuous systems, the optimization of cMPS is known to be a very challenging task,"
258,,Classifying long legal documents using short random chunks,Luis Adrián Cabrera-Diego,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24997v1,https://arxiv.org/pdf/2512.24997v1,arxiv,,"Classifying legal documents is a challenge, besides their specialized vocabulary, sometimes they can be very long. This means that feeding full documents to a Transformers-based models for classification might be impossible, expensive or slow. Thus, we present a legal document classifier based on De"
259,,Noise resilient real-time phase imaging via undetected light,Josué R. León-Torres; Patrick Hendra; Yugant Mukeshbhai Hadiyal; Christopher Spiess; Fabian Steinlechner,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24993v1,https://arxiv.org/pdf/2512.24993v1,arxiv,,Quantum imaging with undetected light has recently emerged as a technique in which quantum correlations and nonlinear interferometry are combined to decouple illumination and detection paths. This approach has been more recently extended and combined with digital phase-shifting holography and off-ax
260,,Universal Audio Generation,Antoine Laurent; Sameer Khurana; Anthony Larcher; Dominik Klement; Mickaël Rouvier,2026,HAL (Le Centre pour la Communication Scientifique Directe),,,,,0,0.000,0.000,,https://openalex.org/W4414932055,https://hal.science/hal-05110014v1/document,openalex,,This report describe the research done during the third ESPERANTO/JSALT workshop from the 10th June 2024 to the 2nd of August 2024.
261,,Systematic node fortification for enhanced supply network resilience: a real-world network approach,Patrick Doege; Kai-Oliver Schocke; Maike Scherrer,2025,Logistics Research,,,,,0,0.000,0.000,10.1108/lore-04-2025-0050,https://openalex.org/W7117749598,https://doi.org/10.1108/lore-04-2025-0050,openalex,,Purpose This study questions the need for more visibility to improve supply chain network resilience (SCNR). It investigates how disruptions propagate through real-world supply chain networks and evaluates the effectiveness of different strategies for fortifying key nodes against such disruptions. T
262,,"Symbolic Expression Processing over Factor-Dense Radix Lattices: Theory, Implementation, and Validation",Edwin Jean-Paul Vening,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.18100879,https://openalex.org/W7117687003,https://doi.org/10.5281/zenodo.18100879,openalex,,"Conceptual Contribution and Architectural Insight This work does not propose an incremental optimization of conventional digital computation, nor does it introduce a new arithmetic unit or instruction set. Instead, it demonstrates a symbolic computation framework in which computation emerges from st"
263,,Multimodal Conflict-Aware and Generative-Enhanced AI for Early Startup Survival and Risk Prediction,Jiaying Xi,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8365925/v1,https://openalex.org/W7117517690,https://www.researchsquare.com/article/rs-8365925/latest.pdf,openalex,,"<title>Abstract</title> Early-stage startups are central to innovation-driven economies, yet their failure rates remain persistently high, with more than half of new ventures not surviving their first three to five years. Accurately assessing the risk of young ventures is challenging because relevan"
264,,Attention-Driven-Multi-Agent-Optimizer,Shichen Zhang,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.18065320,https://openalex.org/W7117411429,https://doi.org/10.5281/zenodo.18065320,openalex,,"# Article **Optimizing Decision-Making Processes Using Deep Reinforcement Learning with Attention Mechanisms and Multi-Agent Systems** ## Description The project titled ""Optimizing Decision-Making Processes Using Deep Reinforcement Learning with Attention Mechanisms and Multi-Agent Systems"" aims to "
265,,Energy-Market-Optimization,Xijun Lin,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.18065371,https://openalex.org/W7117419293,https://doi.org/10.5281/zenodo.18065371,openalex,,# Article **Multi-Agent Systems for Energy Market Optimization and Real-Time Power Trading** ## Description This project presents a novel framework utilizing multi-agent systems for optimizing energy markets and facilitating real-time power trading. The approach addresses the complexities of dynamic
266,,High-fidelity 3D mesh generation from a single sketch using shape constraints,Yingbin Wu; Fubo Wang; Peng Zhao; MingQuan ZHOU; Shengling Geng,2025,Scientific Reports,,,,,0,0.000,0.000,10.1038/s41598-025-30843-3,https://openalex.org/W7117316252,https://doi.org/10.1038/s41598-025-30843-3,openalex,,"Abstract The research on 3D model reconstruction from a single image using deep learning technology has achieved remarkable progress. However, compared with images, sketches lack sufficient visual information, which challenges the reconstruction algorithm’s ability to correctly interpret sketches. H"
267,,LSI Protocol: Logical Structured Intelligence Governance Architecture (v9.01),Yingliang Tan,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.18058675,https://openalex.org/W7117358326,https://doi.org/10.5281/zenodo.18058675,openalex,,"LSI Protocol: Logic-First Architecture (v9.01) Turning Ephemeral Feedback into Persistent Cognition. Abstract The Logical Structured Intelligence (LSI) protocol establishes a deterministic ""Logic-First"" architecture that orthogonally decouples probabilistic generation (LLM) from logical arbitration "
268,,DATA VISUALIZATION AS A FORM OF SCULPTURAL ART,Manivannan Karunakaran; Praney Madan; Sachin Pratap Singh; Peeyush Kumar Gupta; Mohd Faisal,2025,ShodhKosh Journal of Visual and Performing Arts,,,,,0,0.000,0.000,10.29121/shodhkosh.v6.i4s.2025.6863,https://openalex.org/W7117421613,https://doi.org/10.29121/shodhkosh.v6.i4s.2025.6863,openalex,,"Data visualization, the interconnection of information and sculptural art is a new paradigm where information moves out of the digital screens and finds space in the physical world to express itself. This paper examines the conceptual, aesthetic and technological systems that allow the data to be ph"
269,,Interpretable Feature Interaction via Statistical Self-supervised Learning on Tabular Data,Susan Zhang; Haoyi Xiong,2025,Machine Learning Science and Technology,,,,,0,0.000,0.000,10.1088/2632-2153/ae3104,https://openalex.org/W7117251088,https://doi.org/10.1088/2632-2153/ae3104,openalex,,"Abstract In high-stakes scientific contexts, explainable AI is crucial for deriving meaningful insights from complex tabular data. A formidable challenge is ensuring both rigorous statistical guarantees and clear interpretability in feature extraction. While traditional methods like PCA are limited "
270,,Symmaries: Automatic Inference of Formal Security Summaries for Java Programs,Narges Khakpour; Nicolas Berthier,2025,arXiv (Cornell University),,,,,0,0.000,0.000,10.48550/arxiv.2512.20396,https://openalex.org/W7117249337,https://doi.org/10.48550/arxiv.2512.20396,openalex,,"We introduce a scalable, modular, and sound approach for automatically constructing formal security specifications for Java bytecode programs in the form of method summaries. A summary provides an abstract representation of a method's security behavior, consisting of the conditions under which the m"
271,,Sociological Science,,2025,Sociological Science,,,,,47,0.000,0.000,10.15195/issn.2330-6696,https://openalex.org/W4245384152,https://sociologicalscience.com/download/vol_12/march/SocSci_v12_180to201.pdf,openalex,,
272,,Exploring the School Environment Through an Ethnomathematics Approach,Rizqi Retno Asih; Unsiyah Nuzulah; Purnomo Purnomo,2025,Kognitif Jurnal Riset HOTS Pendidikan Matematika,,,,,0,0.000,0.000,10.51574/kognitif.v5i4.4016,https://openalex.org/W4417516287,https://doi.org/10.51574/kognitif.v5i4.4016,openalex,,"Mathematics is often perceived as abstract and disconnected from everyday life, causing students to struggle with topics requiring symbolic representation, such as matrices. This situation indicates the need for learning approaches that connect formal concepts with real experiences, highlighting the"
273,,Why world models fail under intervention:Ontological–causal separation as a necessarystructure,Liang Tian,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8377767/v1,https://openalex.org/W4417479511,https://doi.org/10.21203/rs.3.rs-8377767/v1,openalex,,"<title>Abstract</title> Learning world models that can understand, predict, and act within complex physical environments is a fundamental goal of embodied intelligence. However, many dominant approaches—such as latent video models, Dreamer-style imagination agents, and recent JEPA-based predictive a"
274,,Kernel alignment for unsupervised feature selection via matrix factorization,Ziyuan Lin; Deanna Needell,2025,Sampling Theory Signal Processing and Data Analysis,,,,,0,0.000,0.000,10.1007/s43670-025-00120-5,https://openalex.org/W4417461250,https://link.springer.com/content/pdf/10.1007/s43670-025-00120-5.pdf,openalex,,"Abstract By removing irrelevant and redundant features, feature selection aims to find a good representation of the original features. With the prevalence of unlabeled data, unsupervised feature selection has proven effective in alleviating the so-called curse of dimensionality. Most existing matrix"
275,,Названия одежды как средство лингвосемиотического кодирования концептуальной информации,Людмила Витальевна Дубина; Шухань Дун,2025,ΠΡΑΞΗMΑ Journal of Visual Semiotics,,,,,0,0.000,0.000,10.23951/2312-7899-2025-4-58-78,https://openalex.org/W4417417775,https://doi.org/10.23951/2312-7899-2025-4-58-78,openalex,,"Изучение вестиментарного кода в контексте задач межкультурного обучения требует синтеза лингвистического и семиотического подходов к его описанию. В статье культурный код одежды рассматривается как сложная система, включающая невербальный и вербальный компоненты. В основу представленной модели полож"
276,,CDGaitFusion: a multimodal gait recognition network based on the fusion of commonality patterns and differential features,Siwei Wei; Qi Shi; Feifei Wei; Chunzhi Wang,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8218080/v1,https://openalex.org/W4417431795,https://www.researchsquare.com/article/rs-8218080/latest.pdf,openalex,,"<title>Abstract</title> As a behavioral biometric relying on human walking dynamics, gait recognition enables non-contact and long-range identity verification, making it highly valuable for public security and intelligent monitoring applications. However, its performance in real-world environments o"
277,,Strange Multiplicity: Diverse Patterns of Governance for Canadian Metropolitan Areas,Zack Taylor,2025,Local and urban governance,,,,,0,0.000,0.000,10.1007/978-3-031-99820-1_2,https://openalex.org/W4417355156,https://link.springer.com/content/pdf/10.1007/978-3-031-99820-1_2.pdf,openalex,,"Abstract This chapter relates two scales of governance and political representation that are inextricable, but which are rarely considered together: the metropolitan and the municipal. The contemporary effectiveness and legitimacy of local governance, and the capacity of local institutions to articu"
278,,Neurosymbolische AI unificeren en opschalen: van abstractie tot toepassing,"De Smet, Lennert",2025,Lirias (KU Leuven),,,,,0,0.000,0.000,,https://openalex.org/W7112047987,,openalex,,"The emulation of intelligence in all its aspects is poised to revolutionise our way of living, working and interacting. Its biggest success stories of the last two decades have given us vision models that help healthcare workers with diagnosing diseases more accurately than ever, game-playing models"
279,,CauReL: Dynamic Counterfactual Learning for Precision Drug Repurposing in Alzheimer's Disease,Yanfei Wang; Minghao Zhou; Zhixuan Tang; Chenxi Xiong; Breton M. Asken,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8206648/v1,https://openalex.org/W4417311633,https://www.researchsquare.com/article/rs-8206648/latest.pdf,openalex,,"<title>Abstract</title> Alzheimer’s disease has few effective therapies, and decades of amyloid- and tau-focused trials have delivered only modest benefit with substantial toxicity. Drug repurposing using real-world data offers a faster and lower-risk route to new treatments, yet current approaches "
280,,DeepDOX1: A Dual-Drive Framework Integrating Deep Learning and First-Principles Physics for Drug-Protein Affinity Prediction,Zheng Liu; Hao Sun; Yuliang Wang; Yanliang Ren; Li Rao,2025,,,,,,0,0.000,0.000,10.64898/2025.12.12.693818,https://openalex.org/W4417340199,,openalex,,"Abstract In this work, we present DeepDOX1, a dual-drive drug-protein affinity (DPA) prediction tool features the tight integration of a concise AI architecture and a quantum mechanics based representation. The first-principle physics generated features incorporating the interactions between the dru"
281,,An adaptive hybrid particle swarm optimization and genetic algorithm approach for hyperparameter tuning in convolutional neural networks applied to fine-grained image classification,Priti Vaidya; S. M. Kamalapur,2025,Engineering Research Express,,,,,0,0.000,0.000,10.1088/2631-8695/ae2cee,https://openalex.org/W4417343127,,openalex,,Abstract This study presents a novel adaptive hybrid Particle Swarm Optimization–Genetic Algorithm (PSO-GA) for optimizing the hyperparameters of Convolutional Neural Networks (CNNs) in fine-grained image classification tasks. It is a clever idea to equip the global search power of PSO with the loca
282,,A Multi‐Scale Fusion Transformer Network for Federated Privacy‐Preserving Smart Parking Slot Detection,Jamal Alotaibi,2025,Concurrency and Computation Practice and Experience,,,,,0,0.000,0.000,10.1002/cpe.70506,https://openalex.org/W4417348063,,openalex,,"ABSTRACT The rapid development of smart cities has amplified the need for intelligent parking management systems capable of accurately detecting parking slots and classifying their occupancy status in real time. However, conventional centralized learning approaches often compromise privacy and scala"
283,,Hybrid JEPA-Liquid Neural Architecture for Predictive World Modeling and Recursive Self-Improvement,"Sung hun, Kwag",2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17934305,https://openalex.org/W7115574428,https://doi.org/10.5281/zenodo.17934305,openalex,,Abstract This paper presents a novel hybrid neural architecture that integrates Joint-Embedding Predictive Architecture (JEPA) with Liquid Neural Networks (LNN) for world modeling and recursive self-improvement capabilities. The proposed system addresses critical challenges in autonomous AI systems 
284,,SAGA: Open-World Mobile Manipulation via Structured Affordance Grounding,Kuan Fang; Yuxin Chen; Xinghao Zhu; Farzad Niroui; Lingfeng Sun,2025,arXiv (Cornell University),,,,,0,0.000,0.000,10.48550/arxiv.2512.12842,https://openalex.org/W4417452373,https://arxiv.org/pdf/2512.12842,openalex,,"We present SAGA, a versatile and adaptive framework for visuomotor control that can generalize across various environments, task objectives, and user specifications. To efficiently learn such capability, our key idea is to disentangle high-level semantic intent from low-level visuomotor control by e"
285,,Vision transformers in precision agriculture: A comprehensive survey,Saber Mehdipour; Seyed Abolghasem Mirroshandel; Seyed Amirhossein Tabatabaei,2025,Intelligent Systems with Applications,,,,,0,0.000,0.000,10.1016/j.iswa.2025.200617,https://openalex.org/W7115016258,https://doi.org/10.1016/j.iswa.2025.200617,openalex,,
286,,Mathematical literacy: Parallels between the <scp>PISA</scp> mathematics framework and Vietnam's mathematics curriculum,Hong‐Ha M. Truong; Nguyen Thi Phuong,2025,The Curriculum Journal,,,,,0,0.000,0.000,10.1002/curj.70022,https://openalex.org/W4417292024,,openalex,,"Abstract Mathematical literacy (ML) has gained growing attention in recent years across many countries, as it focuses on equipping individuals with the mathematical understanding necessary to navigate real‐life situations effectively. The paper examines the alignment between Vietnam's mathematics cu"
287,,REPRESENTATION AND ACTUAL MECHANICS IN QUANTUM PHYSICS A Rhythmic–Ontological Clarification,"Jaberi, Afshin",2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17908281,https://openalex.org/W7115017929,https://doi.org/10.5281/zenodo.17908281,openalex,,"Abstract Modern physics has achieved extraordinary predictive success through mathematical formalisms, yet the ontological status of these structures—particularly in quantum mechanics—has remained unresolved. Historically, the micro-world was expected to resemble the macro-world in the form of objec"
288,,A Concentration-Invariant FTIR Chemometric Workflow with Peak-Sparse Representation and Machine-Learning Classification,Otabek Atabaev; Moulay‐Rachid Babaa; Shakhzodbek Samandarov; Asadbek Tajimuratov,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8310607/v1,https://openalex.org/W4417221043,https://www.researchsquare.com/article/rs-8310607/latest.pdf,openalex,,"<title>Abstract</title> Fourier-transform infrared (FTIR) spectroscopy is a widely utilized analytical technique for qualitative identification in chemical, environmental, and industrial contexts. Variability in sample concentration and operator-dependent preprocessing can compromise the reproducibi"
289,,International Spinal Cord Injury Vocational Rehabilitation Basic Data Set,Gillean Hilton; James Middleton; Reuben Escorpizo; Ellen H. Roels; Lisa Ottomanelli,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8114000/v1,https://openalex.org/W4417246888,https://www.researchsquare.com/article/rs-8114000/latest.pdf,openalex,,<title>Abstract</title> <bold>Study design:</bold> International expert working group consensus. <bold>Objective:</bold> To develop an International Spinal Cord Injury (SCI) Vocational Rehabilitation Basic Data Set presenting a standardised format for collection and reporting of a minimal amount of 
290,,An integrated graph neural network model for joint software defect prediction and code quality assessment,Ping Dai; Hongjun Zhu; Jinhua Wu; Hao He,2025,Scientific Reports,,,,,0,0.000,0.000,10.1038/s41598-025-31209-5,https://openalex.org/W4417248379,https://www.nature.com/articles/s41598-025-31209-5_reference.pdf,openalex,,"Current software defect prediction and code quality assessment methods treat these inherently related tasks independently, failing to leverage their complementary information. Existing graph-based approaches lack the ability to jointly model structural dependencies and quality characteristics, limit"
291,,Target-driven optimization of feature representation and model selection for microbiome sequencing data with <i>ritme</i>,A. K. Adamov; Christian L. Müller; Nicholas A. Bokulich,2025,,,,,,0,0.000,0.000,10.64898/2025.12.08.693045,https://openalex.org/W4417252451,https://doi.org/10.64898/2025.12.08.693045,openalex,,"Abstract Microbiome sequencing datasets are sparse, high-dimensional, compositional, and hierarchically structured. Predictive modelling from these data typically relies on ad hoc choices of feature representation, obscuring their impact on performance and biological interpretation. A standardized, "
292,,Capturing Knowledge Dynamics in the Evolving Knowledge Space Graph Using Temporal Relations and Knowledge Aging,László Csépányi-Fürjes; László Kovács,2025,Acta Marisiensis Seria Technologica,,,,,0,0.000,0.000,10.62838/amset-2025-0012,https://openalex.org/W4417376191,https://doi.org/10.62838/amset-2025-0012,openalex,,"Most knowledge representation models in tutoring systems treat knowledge as a static resource. In real world scenarios, knowledge evolves over time as circumstances change. Consequently, the information embedded in a tutoring model may become outdated or require revision, especially in rapidly chang"
293,,HCAG-Net: a novel hierarchical CNN-attention-graph network for multimodal fault diagnosis,Songhua Xiao; Junqi Hou; Longkun Li; Muhammad Jamshaid Khan; Beibei Sun,2025,Measurement Science and Technology,,,,,0,0.000,0.000,10.1088/1361-6501/ae2b97,https://openalex.org/W7114891788,,openalex,,"Abstract This paper proposes a novel hierarchical convolutional neural network (CNN)-attention-graph network (HCAG-Net) for robust multimodal fault diagnosis, designed to address the limitations of traditional methods that rely on single-modality processing and manual fusion strategies. The proposed"
294,,VDAWorld: World Modelling via VLM-Directed Abstraction and Simulation,"O'Mahony, Felix; Cipolla, Roberto; Tewari, Ayush",2025,arXiv (Cornell University),,,,,0,0.000,0.000,10.48550/arxiv.2512.11061,https://openalex.org/W7115599092,https://doi.org/10.48550/arxiv.2512.11061,openalex,,"Generative video models, a leading approach to world modeling, face fundamental limitations. They often violate physical and logical rules, lack interactivity, and operate as opaque black boxes ill-suited for building structured, queryable worlds. To overcome these challenges, we propose a new parad"
295,,Accelerating Prostate Cancer Detection Through Histopathological Image Analysis Using Artificial Intelligence,Anandh Sam Chandra Bose; Cidambi Srinivasan; C Saravanakumar,2025,Microscopy Research and Technique,,,,,0,0.000,0.000,10.1002/jemt.70104,https://openalex.org/W4417273722,,openalex,,"ABSTRACT Prostate cancer is a prevalent and serious health concern, ranking among the most frequently diagnosed cancers and a leading cause of cancer‐related deaths in men worldwide. Early detection and accurate diagnosis are crucial for improving patient outcomes by limiting disease progression. Hi"
296,,Tree structure guided graph neural networks for soft sensing and anomaly regulation,Cheng Lu; Jiusun Zeng; Yi Liu; Jinhui Cai; Ying Liu,2025,Measurement Science and Technology,,,,,0,0.000,0.000,10.1088/1361-6501/ae2aff,https://openalex.org/W7114798565,,openalex,,"Abstract Graph neural networks (GNNs) have emerged as powerful tools for industrial soft sensing, offering the ability to model complex relationships among process variables. However, existing GNN-based soft sensors suffer from two critical limitations: (i) they lack hierarchical modeling capabiliti"
297,,Deny-monotone composition of hierarchical access control policies in distributed systems: a formal algebraic approach,Mahamdou Sidibe,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8290081/v1,https://openalex.org/W4417144553,https://www.researchsquare.com/article/rs-8290081/latest.pdf,openalex,,"<title>Abstract</title> Modern distributed systems built from microservices, multi-cloud deployments and edge nodes rely on fine-grained access control policies that combine attribute-based access control (ABAC) [1] with the principles of Zero Trust Architecture (ZTA) [2]. In practice, access contro"
298,,"Ask, Answer, and Detect: Role-Playing LLMs for Personality Detection with Question-Conditioned Mixture-of-Experts","Lyu, Yifan; Zhang, Liang",2025,arXiv (Cornell University),,,,,0,0.000,0.000,10.48550/arxiv.2512.08814,https://openalex.org/W7114813218,https://doi.org/10.48550/arxiv.2512.08814,openalex,,"Understanding human personality is crucial for web applications such as personalized recommendation and mental health assessment. Existing studies on personality detection predominantly adopt a ""posts -&gt; user vector -&gt; labels"" modeling paradigm, which encodes social media posts into user repre"
299,,Humans rationally balance detailed and temporally abstract world models,Ari E. Kahn; N. D. Daw,2024,bioRxiv,,,,,3,0.000,0.000,10.1038/s44271-024-00169-3,https://www.semanticscholar.org/paper/fec10312b2801c11469ff0da2aad3a9a5bf7a82d,,semantic_scholar,,"How do people model the world’s dynamics to guide mental simulation and evaluate choices? One prominent approach, the Successor Representation (SR), takes advantage of temporal abstraction of future states: by aggregating trajectory predictions over multiple timesteps, the brain can avoid the costs "
300,,Abstract 3519: Reconstructing a latent representation of gene expression from genomic alterations to improve clinical utility of real-world clinicogenomics data,Maayan Baron; Sunil Kumar; Felicia Kuperwaser; Dillon Tracy; Emily Vucic,2024,Cancer Research,,,,,0,0.000,0.000,10.1158/1538-7445.am2024-3519,https://www.semanticscholar.org/paper/ffec34481db10375060930315082ce069d9ae97f,,semantic_scholar,,"
 Background: Molecularly and clinically well-annotated patient datasets are ideal for studying tumor biology and developing robust machine learning (ML) models for predicting outcome and treatment response. These data however rarely exist in real-world settings or in sufficient quantities within re"
301,,Neurosymbolic Graph Enrichment for Grounded World Models,S. D. Giorgis; Aldo Gangemi; Alessandro Russo,2024,Information Processing & Management,,,,,7,0.000,0.000,10.48550/arXiv.2411.12671,https://www.semanticscholar.org/paper/df0f3aff33dbb48b8d095bd09b746108f7b243e4,,semantic_scholar,,The development of artificial intelligence systems capable of understanding and reasoning about complex real-world scenarios is a significant challenge. In this work we present a novel approach to enhance and exploit LLM reactive capability to address complex problems and interpret deeply contextual
302,,Learning Abstract World Models with a Group-Structured Latent Space,Thomas Delliaux; Nguyen-Khanh Vu; Vincent François-Lavet; Elise van der Pol; Emmanuel Rachelson,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2506.01529,https://www.semanticscholar.org/paper/ed7346dcb1fe387a64d5789c79cada4bd42205d4,,semantic_scholar,,"Learning meaningful abstract models of Markov Decision Processes (MDPs) is crucial for improving generalization from limited data. In this work, we show how geometric priors can be imposed on the low-dimensional representation manifold of a learned transition model. We incorporate known symmetric st"
303,,KARNet: Kalman Filter Augmented Recurrent Neural Network for Learning World Models in Autonomous Driving Tasks,Hemanth Manjunatha; A. Pak; Dimitar Filev; P. Tsiotras,2023,arXiv.org,,,,,5,0.000,0.000,10.48550/arXiv.2305.14644,https://www.semanticscholar.org/paper/f5452f1540fa0cd15a84f90f6b6e356d9e4735ed,http://arxiv.org/pdf/2305.14644,semantic_scholar,,Autonomous driving has received a great deal of attention in the automotive industry and is often seen as the future of transportation. The development of autonomous driving technology has been greatly accelerated by the growth of end-to-end machine learning techniques that have been successfully us
304,,Leveraging Open‐Source Geographic Databases to Enhance the Representation of Landscape Heterogeneity in Ecological Models,T. A. Gelmi-Candusso; Peter S. Rodriguez; M. Fidino; Kim Rivera; E. Lehrer,2024,Ecology and Evolution,,,,,5,0.000,0.000,10.1002/ece3.70402,https://www.semanticscholar.org/paper/336a02471c8be13486b67937982d2d49f3d464d0,https://doi.org/10.1002/ece3.70402,semantic_scholar,,"ABSTRACT Wildlife abundance and movement are strongly impacted by landscape heterogeneity, especially in cities which are among the world's most heterogeneous landscapes. Nonetheless, current global land cover maps, which are used as a basis for large‐scale spatial ecological modeling, represent urb"
305,,Scaling Cross-Embodiment World Models for Dexterous Manipulation,Zihao He; Bo Ai; Tongzhou Mu; Yulin Liu; Weikang Wan,2025,arXiv.org,,,,,1,0.000,0.000,10.48550/arXiv.2511.01177,https://www.semanticscholar.org/paper/9cafcf8cb712f3b1e250f750d1031e83a0cd70bb,,semantic_scholar,,"Cross-embodiment learning seeks to build generalist robots that operate across diverse morphologies, but differences in action spaces and kinematics hinder data sharing and policy transfer. This raises a central question: Is there any invariance that allows actions to transfer across embodiments? We"
306,,SketchAA: Abstract Representation for Abstract Sketches,Lan Yang; Kaiyue Pang; Honggang Zhang; Yi-Zhe Song,2021,IEEE International Conference on Computer Vision,,,,,24,0.000,0.000,10.1109/ICCV48922.2021.00994,https://www.semanticscholar.org/paper/53f14a3c0cdc26793b32a17cad8687b8530660cd,,semantic_scholar,,"What makes free-hand sketches appealing for humans lies with its capability as a universal tool to depict the visual world. Such flexibility at human ease, however, introduces abstract renderings that pose unique challenges to computer vision models. In this paper, we propose a purpose-made sketch r"
307,,Graphical representation of global water models,Hannes Müller Schmied; S. Gosling; Marlo Garnsworthy; Laura Müller; C. Telteu,2025,Geoscientific Model Development,,,,,4,0.000,0.000,10.5194/gmd-18-2409-2025,https://www.semanticscholar.org/paper/ec414f79640cde11533c659c35c1f3d57c2ed60b,,semantic_scholar,,"Abstract. Numerical models are simplified representations of the real world at a finite level of complexity. Global water models are used to simulate the terrestrial part of the global water cycle, and their outputs contribute to the evaluation of important natural and societal issues, including wat"
308,,World Models and Attention for Reinforcement Learning,David R Ha,2021,IEEE Symposium on Artificial Life,,,,,0,0.000,0.000,10.1162/isal_a_00471,https://www.semanticscholar.org/paper/61df4b1589e0c96df667ab634c4764170903a064,,semantic_scholar,,"Keynote Abstract Consciousness and the concept of internal mental models are foundational topics in neuroscience and psychology. Yet, we do not understand them well enough to engineer artificial lifeforms that are conscious. In this talk, I will be discussing a line of work on developing “world model"
309,,Synthesis of historical reservoir operations from 1980 to 2020 for the evaluation of reservoir representation in large-scale hydrologic models,J. Steyaert; L. Condon,2024,Hydrology and Earth System Sciences,,,,,10,0.000,0.000,10.5194/hess-28-1071-2024,https://www.semanticscholar.org/paper/27ac5dcff3b47e1513433d72014da40d7d1f8438,,semantic_scholar,,"Abstract. All the major river systems in the contiguous United States (CONUS) (and many in the world) are impacted by dams, yet reservoir operations remain difficult to quantify and model due to a lack of data. Reservoir operation data are often inaccessible or distributed across many local operatin"
310,,Impact of improved representation of volatile organic compound emissions and production of NOx reservoirs on modeled urban ozone production,K. Travis; B. Nault; James H. Crawford; Kelvin H. Bates; Donald R. Blake,2024,Atmospheric Chemistry and Physics,,,,,8,0.000,0.000,10.5194/acp-24-9555-2024,https://www.semanticscholar.org/paper/57ea03a44508592faa6087d446ce34b63229ea99,,semantic_scholar,,"Abstract. The fraction of urban volatile organic compound (VOC) emissions attributable to fossil fuel combustion has been declining in many parts of the world, resulting in a need to better constrain other anthropogenic sources of these emissions. During the National Institute of Environmental Resea"
311,,Simple Orthogonal Graph Representation Learning (Student Abstract),Taoyong Cui; Yuhan Dong,2024,AAAI Conference on Artificial Intelligence,,,,,1,0.000,0.000,10.1609/aaai.v38i21.30430,https://www.semanticscholar.org/paper/db73d1cb2c06a45537250c717efe90d5bb7d828a,https://ojs.aaai.org/index.php/AAAI/article/download/30430/32509,semantic_scholar,,"Graph neural networks (GNNs) have attracted significant interest recently since they can effectively process and analyze graph-structured data commonly found in real-world applications. However, the predicament that GNNs are difficult to train becomes worse as the layers increase. The essence of thi"
312,,"About a Range of Metaphorical Meanings in the Representation 
of the Phenomenon of «Language» in the Book «Herausmit der Sprache» by A. Thalmayr",Lilia Balakina,2023,Izvestia of Smolensk State University,,,,,0,0.000,0.000,10.35785/2072-9464-2023-62-113-122,https://www.semanticscholar.org/paper/a68cb7cd29db1562b36fd6b250d0ee63cba49114,https://doi.org/10.35785/2072-9464-2023-62-113-122,semantic_scholar,,"The article examines the metaphorical models used by the famous German writer, poet, translator Andreas Thalmayr when describing the German language in his book «Heraus mit der Sprache. Ein bisschen Deutsch für Deutsche, Österreicher, Schweizer und andere Aus- und Inländer». Attention to language as"
313,,METAPHORICAL REPRESENTATION OF THE CONCEPT OF MIND IN MODERN FICTION,Ksenia Andreevna Kuzmicheva; Lyudmila Leonidovna Shevchenko,2025,Язык: мультидисциплинарность научного знания,,,,,0,0.000,0.000,10.37386/2949-3307-2025-8-4,https://www.semanticscholar.org/paper/5757c0f999c6bd769e3125ce5f3576b19cbc12ef,,semantic_scholar,,The article is referred to the sphere of cognitive linguistics and presents an attempt to describe the basic metaphorical models representing the concept of MIND in the modern fiction. The work is based on the definition of metaphor as a means of conceptualization and a unique cognitive mechanism th
314,,Relational Causal Models with Cycles: Representation and Reasoning,Ragib Ahsan; D. Arbour; E. Zheleva,2022,CLEaR,,,,,4,0.000,0.000,,https://www.semanticscholar.org/paper/79cd8ce40e351e554c45316010ccbafb6c7d9634,,semantic_scholar,,"Causal reasoning in relational domains is fundamental to studying real-world social phenomena in which individual units can influence each other’s traits and behavior. Dynamics between interconnected units can be represented as an instantiation of a relational causal model; however, causal reasoning "
315,,Deep Representation Debiasing via Mutual Information Minimization and Maximization (Student Abstract),Ruijiang Han; Wei Wang; Yuxi Long; J. Peng,2022,AAAI Conference on Artificial Intelligence,,,,,1,0.000,0.000,10.1609/aaai.v36i11.21619,https://www.semanticscholar.org/paper/052cbf08c62ee03c5cef3a1e8d929be607454491,https://ojs.aaai.org/index.php/AAAI/article/download/21619/21368,semantic_scholar,,"Deep representation learning has succeeded in several fields. However, pre-trained deep representations are usually biased and make downstream models sensitive to different attributes. In this work, we propose a post-processing unsupervised deep representation debiasing algorithm, DeepMinMax, which "
316,,UNCERTAINTY REPRESENTATION AND QUANTIFICATION OF 3D BUILDING MODELS,Q. Zou; Monika Sester,2022,"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",,,,,3,0.000,0.000,10.5194/isprs-archives-xliii-b2-2022-335-2022,https://www.semanticscholar.org/paper/b13bf26b9f77595c6de3f0e418e27e45448a132e,https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/335/2022/isprs-archives-XLIII-B2-2022-335-2022.pdf,semantic_scholar,,"Abstract. The quality of environmental perception is of great interest for localization tasks in autonomous systems. Maps, generated from the sensed information, are often used as additional spatial references in these applications. The quantification of the map uncertainties gives an insight into h"
317,,Compact Abstract Graphs for Detecting Code Vulnerability with GNN Models,Yuxuan Luo; Weifeng Xu; Dianxiang Xu,2022,Asia-Pacific Computer Systems Architecture Conference,,,,,19,0.000,0.000,10.1145/3564625.3564655,https://www.semanticscholar.org/paper/32469361091deb75ee738377e84175e0db3f5b28,,semantic_scholar,,
318,,Abstract 4366996: Forecasting the Onset of Atrial Fibrillation in the Intensive Care Unit Using Real-World Telemetry Data,D. Howarth; Raghavan Murugan; Robert Parker; V. Herasevich; Kianoush B. Kashani,2025,Circulation,,,,,0,0.000,0.000,10.1161/circ.152.suppl_3.4366996,https://www.semanticscholar.org/paper/425a82174cfb58edb1bedb962804708645335c3c,,semantic_scholar,,"
 Background:
 Paroxysmal atrial fibrillation (AF) is a common arrhythmogenic complication in the intensive care unit (ICU) associated with significant costs and morbidity. AF detection models in the literature have utilized entropic analyses of telemetry to diagnose AF, but they have not been utili"
319,,Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution,Rong Ding; S. T. Oever; Andrea E. Martin,2024,Journal of Cognitive Neuroscience,,,,,2,0.000,0.000,10.1162/jocn_a_02163,https://www.semanticscholar.org/paper/84bc6ba8a5522bb114f9e2ffdc3a41b89b456c91,,semantic_scholar,,"Abstract Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities "
320,,Dense Captioning Using Abstract Meaning Representation,A. M. S. A. Neto; Helena de Medeiros Caseli; Tiago A. Almeida,2020,Brazilian Conference on Intelligent Systems,,,,,3,0.000,0.000,10.1007/978-3-030-61377-8_31,https://www.semanticscholar.org/paper/bc7cc5f9e93d59fa6281c2299b65b1021fa0f0b4,,semantic_scholar,,
321,,"Representation of Muslim Women as Seen in American Advertisements: Ability, Egalitarianism, and Resistance",Moona Maghfirah,2020,,,,,,2,0.000,0.000,10.18196/aiijis.2020.0110.1-21,https://www.semanticscholar.org/paper/b70c2a7e85797795f6c59b698db4e5ee1d30fe76,https://doi.org/10.18196/aiijis.2020.0110.1-21,semantic_scholar,,"Abstract:  Since Muslimah fashion has risen in the world, many companies are showing Muslim wom e n who wear veiling their advertisements, including American brands advertisements. They are Nike, American Eagle, Covergirl, Fenty Beauty, and Gap. This case is important to be discussed, because it is "
322,,Characterizing behavioural differentiation in gene regulatory networks with representation graphs,Juris Viksna; Kārlis Čerāns; Lelde Lace; Gatis Melkus,2024,NAR Genomics and Bioinformatics,,,,,0,0.000,0.000,10.1093/nargab/lqae102,https://www.semanticscholar.org/paper/777ab57ca33d59c00ef613bffd5bfa867d20e65e,,semantic_scholar,,"Abstract We introduce the formal notion of representation graphs, encapsulating the state space structure of gene regulatory network models in a compact and concise form that highlights the most significant features of stable states and differentiation processes leading to distinct stability regions"
323,,Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions,Joren Janzing; N. Wanders; Marit van Tiel; Barry van Jaarsveld; D. Karger,2025,Hydrology and Earth System Sciences,,,,,3,0.000,0.000,10.5194/hess-29-7041-2025,https://www.semanticscholar.org/paper/524b6f0a202b221c2510f1a8d03ba27d91bb9754,,semantic_scholar,,"Abstract. Many of the world's major rivers originate in mountain regions, and a large fraction of the global population relies on these regions for their water supply. The hydrological cycle of mountain regions and their dependent downstream regions are often studied using large-scale to global hydr"
324,,Representation and Idealization: Diagrammatic Models in the Early Studies of the Spatial Structure of Periodic Markets in Rural China,Hsiang-Ke Chao,2020,"East Asian Science, Technology and Society: an International Journal",,,,,1,0.000,0.000,10.1215/18752160-8538388,https://www.semanticscholar.org/paper/0045b5c11fba7d90822d7e2631fcd02d72232b8b,,semantic_scholar,,Abstract This article explores how diagrams are performed in actual scientific practice by examining two studies of the structure of periodic markets in rural China before and during the World War II. These are Ching-Kun Yang’s pioneering study of systematic field observations of Chinese periodic ma
325,,ACT-JEPA: Joint-Embedding Predictive Architecture Improves Policy Representation Learning,Aleksandar Vujinović; Aleksandar Kovacevic,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2501.14622,https://www.semanticscholar.org/paper/5b5b07005a76bac012e687cd96c87adbbf12a46f,,semantic_scholar,,
326,,ACT-JEPA: Novel Joint-Embedding Predictive Architecture for Efficient Policy Representation Learning,Aleksandar Vujinović; Aleksandar Kovacevic,2025,,,,,,0,0.000,0.000,,https://www.semanticscholar.org/paper/c46f0114e99edefb42580106bd1080222d72e7d0,,semantic_scholar,,"Learning efficient representations for decision-making policies is a challenge in imitation learning (IL). Current IL methods require expert demonstrations, which are expensive to collect. Consequently, they often have underdeveloped world models. Self-supervised learning (SSL) offers an alternative"
327,,Marker versus filter: team focused interaction in complex cognitive representation models,S. Schneider; M. Hanrieder; A. Nürnberger,2020,,,,,,0,0.000,0.000,,https://www.semanticscholar.org/paper/bb0482674891996edeca3df933c185cf95f74205,,semantic_scholar,,
328,,Preference-Based Abstract Argumentation for Case-Based Reasoning (with Appendix),Adam Gould; Guilherme Paulino-Passos; S. Dadhania; Matthew Williams; F. Toni,2024,International Conference on Principles of Knowledge Representation and Reasoning,,,,,4,0.000,0.000,10.48550/arXiv.2408.00108,https://www.semanticscholar.org/paper/b4e58e98100b0e5a0f3508089292724809beb0a2,,semantic_scholar,,"In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences with Abstract Argumentation and Case-Based Reasoning (CBR). Specifically, we introduce Preference-Based Abstract Argume"
329,,An Extensive Study on Model Architecture and Program Representation in the Domain of Learning-based Automated Program Repair,Dániel Horváth; Viktor Csuvik; T. Gyimóthy; László Vidács,2023,APR,,,,,4,0.000,0.000,10.1109/APR59189.2023.00013,https://www.semanticscholar.org/paper/a26d1bb6b614e0579d5e70dee6d9ba044ebdcc3a,https://publicatio.bibl.u-szeged.hu/27453/1/apr-proc.pdf,semantic_scholar,,"Bug fixing is one of the most time-consuming and resource-intensive tasks in the software development life cycle. Automated Program Repair (APR) might be able to help in this process, but it still has to overcome many obstacles. Deep learning models have shown promise for automated program repair in"
330,,Granular-ball representation-based two-stage deep learning model for text classification,Wenbin Qian; Ying He; Xingxing Cai; Jintao Huang,2025,Applied intelligence (Boston),,,,,0,0.000,0.000,10.1007/s10489-025-07010-2,https://www.semanticscholar.org/paper/5dd43a62ace6c47d39fdc4c84cd75ac7df4954d7,,semantic_scholar,,
331,,Survey on Embedding Models for Knowledge Graph and its Applications,Manita Pote,2024,arXiv.org,,,,,2,0.000,0.000,10.48550/arXiv.2404.09167,https://www.semanticscholar.org/paper/cda81da1f54f9d9854e28e2e9b289b7199ea4e59,,semantic_scholar,,"Knowledge Graph (KG) is a graph based data structure to represent facts of the world where nodes represent real world entities or abstract concept and edges represent relation between the entities. Graph as representation for knowledge has several drawbacks like data sparsity, computational complexi"
332,,Local community beads: Representation to enhance learning about the Bohr structure in science,Angelius Kanyanga Liveve; M. Mukwambo,2025,Aquademia,,,,,0,0.000,0.000,10.29333/aquademia/16291,https://www.semanticscholar.org/paper/7abdfcbb408bb56cd6531e58abb478e8c4b851b6,,semantic_scholar,,"This paper explored the ways learners respond to and express themselves while interacting with cultural artifacts or cultural realia, for instance, beads, that can be used to mediate the learning of physical science concepts. The study mandates that a culturally responsive pedagogy be used to teach "
333,,Advancing New Governance Models for Gender Data in Climate Resilience Funding,Jane Ezirigwe,2024,The Law and Development Review,,,,,1,0.000,0.000,10.1515/ldr-2024-0110,https://www.semanticscholar.org/paper/3cb6b1d8c6c6b638440c9d28dfa8b7961b11ec8e,,semantic_scholar,,"Abstract Globally, between USD 850 to USD 940 billion was allocated for 2021 climate finance. However, a mere 0.01 percent of this was directed towards projects addressing both climate change and women’s rights. Unfortunately, the climate crisis is not gender-neutral. Yet, gender data analysis and t"
334,,Foundational Models for 3D Point Clouds: A Survey and Outlook,Vishal G. Thengane; Xiatian Zhu; A. Bouzerdoum; S. L. Phung; Yunpeng Li,2025,arXiv.org,,,,,8,0.000,0.000,10.48550/arXiv.2501.18594,https://www.semanticscholar.org/paper/1139070c61a690bf98ce81e440293e8d2dc5cf57,,semantic_scholar,,"The 3D point cloud representation plays a crucial role in preserving the geometric fidelity of the physical world, enabling more accurate complex 3D environments. While humans naturally comprehend the intricate relationships between objects and variations through a multisensory system, artificial in"
335,,AbSynth: Using Abstract Image Synthesis for Synthetic Training,D. Penk; Maik Horn; Christoph Strohmeyer; Bernhard Egger; Marc Stamminger,2024,VISIGRAPP : VISAPP,,,,,0,0.000,0.000,10.5220/0012431400003660,https://www.semanticscholar.org/paper/b806b8ae8c1f135500d1ecb0b8161573cd069a47,https://doi.org/10.5220/0012431400003660,semantic_scholar,,": We present a novel pipeline for training neural networks to tackle geometry-induced vision tasks, relying solely on synthetic training images generated from (geometric) CAD models of the objects under consideration. Instead of aiming for photorealistic renderings, our approach maps both synthetic "
336,,Multi-Grained Semantics-Aware Graph Neural Networks (Extended abstract),Zhiqiang Zhong; Cheng-Te Li; Jun Pang,2024,IEEE International Conference on Data Engineering,,,,,0,0.000,0.000,10.1109/ICDE60146.2024.00477,https://www.semanticscholar.org/paper/46d6259b214c954bfdc67c27ad1cf5aec0aea7b2,,semantic_scholar,,Graph Neural Networks (GNNs) are powerful techniques in representation learning for graphs and have been increasingly deployed in a multitude of different applications that involve node- and graph-wise tasks. Most existing studies solve either the node-wise task or the graph-wise task independently 
337,,Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP6 models,A. Katzenberger; J. Schewe; J. Pongratz; A. Levermann,2021,,,,,,165,0.000,0.000,10.5194/ESD-12-367-2021,https://www.semanticscholar.org/paper/0bac98e3de9ed4c0bd11d22fef5db279cd49f8cc,https://esd.copernicus.org/articles/12/367/2021/esd-12-367-2021.pdf,semantic_scholar,,"Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess "
338,,Compact Models for Some Cluster Problems on Node-Colored Graphs,Roberto Montemanni; Derek H. Smith; P. Luangpaiboon; P. Aungkulanon,2025,Algorithms,,,,,0,0.000,0.000,10.3390/a18120759,https://www.semanticscholar.org/paper/21362fb29fa62cee7e7c1263f6263c7305111d43,,semantic_scholar,,"Three optimization problems based on node-colored undirected graphs are the subject of the present study. These problems model real-world applications in several domains, such as cybersecurity, bioinformatics, and social networks, although they have a similar abstract representation. In all of the p"
339,,BYOS: Knowledge-driven Large Language Models Bring Your Own Operating System More Excellent,Hongyu Lin; Yuchen Li; Haoran Luo; Kaichun Yao; Libo Zhang,2025,arXiv.org,,,,,2,0.000,0.000,10.48550/arXiv.2503.09663,https://www.semanticscholar.org/paper/404d0035005694e7a72706f84add310c823aead8,,semantic_scholar,,"Operating System (OS) kernel tuning involves systematically adjusting kernel configurations to optimize system performance. Despite recent advancements in large language models (LLMs), kernel tuning remains a critical challenge due to: (1) the semantic gap between abstract tuning objective and concr"
340,,Active Proxy Dashboard: Binding Physical Referents and Abstract Data Representations in Situated Visualization through Tangible Interaction,K. Satriadi; Barrett Ens; Sarah Goodwin; Tim Dwyer,2023,CHI Extended Abstracts,,,,,7,0.000,0.000,10.1145/3544549.3585797,https://www.semanticscholar.org/paper/717368bfd2f48cd39259dbc29fbedba2f66fda38,https://doi.org/10.1145/3544549.3585797,semantic_scholar,,Myriad systems have been proposed in recent years involving situated visualization with tangible scale models as proxies for physical referents. Most of these focus on static placements of scale models that mimic their real-world arrangement. While such static placement is useful to show the spatial
341,,War and Difference: Models of Reading in Vasilij Grossman’s Novel Life and Fate,Josefina Lundblad Janjic,2025,Scando-Slavica,,,,,0,0.000,0.000,10.1080/00806765.2025.2479194,https://www.semanticscholar.org/paper/83e4434dc0cceb05c981152cbb888ba7dc0d2640,,semantic_scholar,,"ABSTRACT This paper explores the novel Life and Fate (Žiznʹ i sudʹba, 1960) by Vasilij Grossman through its intertextual dialogue with past literature. A reporter during World War II who brought Lev Tolstoj’s War and Peace with him to read at the front, Grossman modeled his representation of the twe"
342,,Historical and future changes in air pollutants from CMIP6 models,S. Turnock; R. Allen; M. Andrews; S. Bauer; L. Emmons,2020,Atmospheric Chemistry and Physics,,,,,208,0.000,0.000,10.5194/acp-2019-1211,https://www.semanticscholar.org/paper/fadd29ed014561c829b2fe296d102b7dad9ef9d3,https://acp.copernicus.org/articles/20/14547/2020/acp-20-14547-2020.pdf,semantic_scholar,,"Abstract. Poor air quality is currently responsible for large impacts on human health across the world. In
addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in
diameter (PM2.5) are also radiatively active in the atmosphere and can influence
Earth's climate. It is import"
343,,ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning,Vy Vo; Lizhen Qu; Tao Feng; Yuncheng Hua; Xiaoxi Kang,2025,North American Chapter of the Association for Computational Linguistics,,,,,0,0.000,0.000,10.48550/arXiv.2502.08148,https://www.semanticscholar.org/paper/8c92405450a740f1e92b78ac157cb12e65c47a78,,semantic_scholar,,"Identifying cause-and-effect relationships is critical to understanding real-world dynamics and ultimately causal reasoning. Existing methods for identifying event causality in NLP, including those based on Large Language Models (LLMs), exhibit difficulties in out-of-distribution settings due to the"
344,,Evaluating the performance of CMIP6 models in simulating Southern Ocean biogeochemistry,Ming Cheng; N. Maher; Michael J. Ellwood,2025,Biogeosciences,,,,,0,0.000,0.000,10.5194/bg-22-7269-2025,https://www.semanticscholar.org/paper/973701a73ae8d5445872b6cba761eff7e8982075,,semantic_scholar,,"Abstract. The Southern Ocean plays a vital role in global biogeochemical cycles, yet comprehensive assessments of its representation in Earth System Models (ESMs) are still limited. This study evaluates the performance of 14 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating "
345,,Evaluating and Optimizing the Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on the CAT Benchmark,H. Phan; Ali Jannesari,2023,International Conference on Information and Knowledge Management,,,,,3,0.000,0.000,10.1145/3583780.3614869,https://www.semanticscholar.org/paper/f6d8199f41015fe6cbba03dc513cfae5a9f663e8,https://dl.acm.org/doi/pdf/10.1145/3583780.3614869,semantic_scholar,,Neural Machine Translation (NMT) is widely applied in software engineering tasks. The effectiveness of NMT for code retrieval relies on the ability to learn from the sequence of tokens in the source language to the sequence of tokens in the target language. While NMT performs well in pseudocode-to-c
346,,Learning to Play Atari in a World of Tokens,Pranav Agarwal; Sheldon Andrews; Samira Ebrahimi Kahou,2024,International Conference on Machine Learning,,,,,5,0.000,0.000,10.48550/arXiv.2406.01361,https://www.semanticscholar.org/paper/c91e2861c2b09215ed053fe064b0cbf3b9a9d353,,semantic_scholar,,"Model-based reinforcement learning agents utilizing transformers have shown improved sample efficiency due to their ability to model extended context, resulting in more accurate world models. However, for complex reasoning and planning tasks, these methods primarily rely on continuous representation"
347,,Code Aggregate Graph: Effective Representation for Graph Neural Networks to Detect Vulnerable Code,H. Nguyen; Junjun Zheng; A. Inomata; T. Uehara,2022,IEEE Access,,,,,8,0.000,0.000,10.1109/ACCESS.2022.3216395,https://www.semanticscholar.org/paper/6e4c3a73c13ab38b349b7d9b583f59053221098f,https://ieeexplore.ieee.org/ielx7/6287639/6514899/09927184.pdf,semantic_scholar,,"Deep learning, especially graph neural networks (GNNs), provides efficient, fast, and automated methods to detect vulnerable code. However, the accuracy could be improved as previous studies were limited by existing code representations. Additionally, the diversity of embedding techniques and GNN mo"
348,,Precipitation–fire functional interactions control biomass stocks and carbon exchanges across the world's largest savanna,Mathew Williams; D. Milodowski; T. Smallman; Kyle G. Dexter; G. Hegerl,2025,Biogeosciences,,,,,8,0.000,0.000,10.5194/bg-22-1597-2025,https://www.semanticscholar.org/paper/ee0294942283fcbba475f5414d0f7876b2447910,https://doi.org/10.5194/bg-22-1597-2025,semantic_scholar,,"Abstract. Southern African woodlands (SAW) are the world's largest savanna, covering ∼ 3 M km2, but their carbon balance and its interactions with climate and disturbance are poorly understood. Here we address three issues that hinder regional efforts to address international climate agreements: pro"
349,,Efficiently Estimating Data Efficiency for Language Model Fine-tuning,Gyung Hyun Je; Colin Raffel,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24991v1,https://arxiv.org/pdf/2512.24991v1,arxiv,,"While large language models (LLMs) demonstrate reasonable zero-shot capability across many downstream tasks, fine-tuning is a common practice to improve their performance. However, a task's data efficiency--i.e., the number of fine-tuning examples needed to achieve a desired level of performance--is"
350,,Best Practices for Modelling Electrides,Lee A. Burton,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24989v1,https://arxiv.org/pdf/2512.24989v1,arxiv,,"Materials in which electrons occupy interstitial sites as anions are called electrides and exhibit unusual dimensionality-dependent electronic behavior. These properties make electrides attractive for catalysis, transparent conductors, and emergent quantum phenomena, yet their theoretical treatment "
351,,"Wall crossing, string networks and quantum toroidal algebras",Yegor Zenkevich,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24988v1,https://arxiv.org/pdf/2512.24988v1,arxiv,,"We investigate BPS states in 4d N=4 supersymmetric Yang-Mills theory and the corresponding (p, q) string networks in Type IIB string theory. We propose a new interpretation of the algebra of line operators in this theory as a tensor product of vector representations of a quantum toroidal algebra, wh"
352,,PhysTalk: Language-driven Real-time Physics in 3D Gaussian Scenes,Luca Collorone; Mert Kiray; Indro Spinelli; Fabio Galasso; Benjamin Busam,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24986v1,https://arxiv.org/pdf/2512.24986v1,arxiv,,"Realistic visual simulations are omnipresent, yet their creation requires computing time, rendering, and expert animation knowledge. Open-vocabulary visual effects generation from text inputs emerges as a promising solution that can unlock immense creative potential. However, current pipelines lack "
353,,DarkEQA: Benchmarking Vision-Language Models for Embodied Question Answering in Low-Light Indoor Environments,Yohan Park; Hyunwoo Ha; Wonjun Jo; Tae-Hyun Oh,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24985v1,https://arxiv.org/pdf/2512.24985v1,arxiv,,"Vision Language Models (VLMs) are increasingly adopted as central reasoning modules for embodied agents. Existing benchmarks evaluate their capabilities under ideal, well-lit conditions, yet robust 24/7 operation demands performance under a wide range of visual degradations, including low-light cond"
354,,Lindbladian PT phase transitions,Yuma Nakanishi; Tomohiro Sasamoto,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24981v1,https://arxiv.org/pdf/2512.24981v1,arxiv,,"A parity-time (PT) transition is a spectral transition characteristic of non-Hermitian generators; it typically occurs at an exceptional point, where multiple eigenvectors coalesce. The concept of a PT transition has been extended to Markovian open quantum systems, which are described by the GKSL eq"
355,,A Modal Logic for Possibilistic Reasoning with Fuzzy Formal Contexts,Prosenjit Howlader; Churn-Jung Liau,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24980v1,https://arxiv.org/pdf/2512.24980v1,arxiv,,We introduce a two-sort weighted modal logic for possibilistic reasoning with fuzzy formal contexts. The syntax of the logic includes two types of weighted modal operators corresponding to classical necessity ($\Box$) and sufficiency ($\boxminus$) modalities and its formulas are interpreted in fuzzy
356,,Attribution-Guided Distillation of Matryoshka Sparse Autoencoders,Cristina P. Martin-Linares; Jonathan P. Ling,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24975v1,https://arxiv.org/pdf/2512.24975v1,arxiv,,"Sparse autoencoders (SAEs) aim to disentangle model activations into monosemantic, human-interpretable features. In practice, learned features are often redundant and vary across training runs and sparsity levels, which makes interpretations difficult to transfer and reuse. We introduce Distilled Ma"
357,,Hierarchical Deformation Planning and Neural Tracking for DLOs in Constrained Environments,Yunxi Tang; Tianqi Yang; Jing Huang; Xiangyu Chu; Kwok Wai Samuel Au,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24974v1,https://arxiv.org/pdf/2512.24974v1,arxiv,,"Deformable linear objects (DLOs) manipulation presents significant challenges due to DLOs' inherent high-dimensional state space and complex deformation dynamics. The wide-populated obstacles in realistic workspaces further complicate DLO manipulation, necessitating efficient deformation planning an"
358,,From Complex-Analytic Models to Sparse Domination: A Dyadic Approach of Hypersingular Operators via Bourgain's Interpolation Method,Bingyang Hu; Xiaojing Zhou,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24972v1,https://arxiv.org/pdf/2512.24972v1,arxiv,,"Motivated by the work of Cheng--Fang--Wang--Yu on the hypersingular Bergman projection, we develop a real-variable and dyadic framework for hypersingular operators in regimes where strong-type estimates fail at the critical line. The main new input is a hypersingular sparse domination principle comb"
359,,Evaluating the Impact of Compression Techniques on the Robustness of CNNs under Natural Corruptions,Itallo Patrick Castro Alves Da Silva; Emanuel Adler Medeiros Pereira; Erick de Andrade Barboza; Baldoino Fonseca dos Santos Neto; Marcio de Medeiros Ribeiro,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24971v1,https://arxiv.org/pdf/2512.24971v1,arxiv,,"Compressed deep learning models are crucial for deploying computer vision systems on resource-constrained devices. However, model compression may affect robustness, especially under natural corruption. Therefore, it is important to consider robustness evaluation while validating computer vision syst"
360,,Large language models and the entropy of English,Colin Scheibner; Lindsay M. Smith; William Bialek,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24969v1,https://arxiv.org/pdf/2512.24969v1,arxiv,,"We use large language models (LLMs) to uncover long-ranged structure in English texts from a variety of sources. The conditional entropy or code length in many cases continues to decrease with context length at least to $N\sim 10^4$ characters, implying that there are direct dependencies or interact"
361,,The Impact of LLMs on Online News Consumption and Production,Hangcheng Zhao; Ron Berman,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24968v1,https://arxiv.org/pdf/2512.24968v1,arxiv,,Large language models (LLMs) change how consumers acquire information online; their bots also crawl news publishers' websites for training data and to answer consumer queries; and they provide tools that can lower the cost of content creation. These changes lead to predictions of adverse impact on n
362,,Cosmic Himalayas in CROCODILE : Probing the Extreme Quasar Overdensities by Count-in-Cells analysis and Nearest Neighbor Distribution,Yuto Kuwayama; Yongming Liang; Kentaro Nagamine; Yuri Oku; Daisuke Nishihama,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24966v1,https://arxiv.org/pdf/2512.24966v1,arxiv,,"The recently reported Cosmic Himalayas (CH) -- an extreme quasar overdensity at z~2 -- poses an apparent challenge to the Lambda CDM framework, with a reported significance of 16.9-sigma under Gaussian assumptions. Such an event appears improbably rare, with a formal probability of P ~ 10^-68. In th"
363,,ShowUI-$π$: Flow-based Generative Models as GUI Dexterous Hands,Siyuan Hu; Kevin Qinghong Lin; Mike Zheng Shou,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24965v1,https://arxiv.org/pdf/2512.24965v1,arxiv,,"Building intelligent agents capable of dexterous manipulation is essential for achieving human-like automation in both robotics and digital environments. However, existing GUI agents rely on discrete click predictions (x,y), which prohibits free-form, closed-loop trajectories (e.g. dragging a progre"
364,,Fundamental Limits for Near-Field Sensing -- Part II: Wide-Band Systems,Tong Wei; Kumar Vijay Mishra; Bhavani Shankar M. R.; Björn Ottersten,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24962v1,https://arxiv.org/pdf/2512.24962v1,arxiv,,"Near-field sensing with extremely large-scale antenna arrays (ELAAs) in practical 6G systems is expected to operate over broad bandwidths, where delay, Doppler, and spatial effects become tightly coupled across frequency. The purpose of this and the companion paper (Part I) is to develop the unified"
365,,From Principles to Effective Models: A Constructive Framework for Effective Covariant Actions with a Unique Vacuum Solution,Kristina Giesel; Hongguang Liu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24960v1,https://arxiv.org/pdf/2512.24960v1,arxiv,,"The absence of Birkhoff's theorem in effective quantum gravity models leads to a fundamental ambiguity in the vacuum sector, where a priori no unique vacuum solution exists. As a result, phenomenological investigations of the physical implications of these models have been made more difficult. We ad"
366,,Semi-overlapping Multi-bandit Best Arm Identification for Sequential Support Network Learning,András Antos; András Millinghoffer; Péter Antal,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24959v1,https://arxiv.org/pdf/2512.24959v1,arxiv,,"Many modern AI and ML problems require evaluating partners' contributions through shared yet asymmetric, computationally intensive processes and the simultaneous selection of the most beneficial candidates. Sequential approaches to these problems can be unified under a new framework, Sequential Supp"
367,,Fundamental Limits for Near-Field Sensing -- Part I: Narrow-Band Systems,Tong Wei; Kumar Vijay Mishra; Bhavani Shankar M. R.; Björn Ottersten,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24958v1,https://arxiv.org/pdf/2512.24958v1,arxiv,,"Extremely large-scale antenna arrays (ELAAs) envisioned for 6G enable high-resolution sensing. However, the ELAAs worked in extremely high frequency will push operation into the near-field region, where spherical wavefronts invalidate classical far-field models and alter fundamental estimation limit"
368,,AMAP Agentic Planning Technical Report,Yulan Hu; Xiangwen Zhang; Sheng Ouyang; Hao Yi; Lu Xu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24957v1,https://arxiv.org/pdf/2512.24957v1,arxiv,,"We present STAgent, an agentic large language model tailored for spatio-temporal understanding, designed to solve complex tasks such as constrained point-of-interest discovery and itinerary planning. STAgent is a specialized model capable of interacting with ten distinct tools within spatio-temporal"
369,,MSACL: Multi-Step Actor-Critic Learning with Lyapunov Certificates for Exponentially Stabilizing Control,Yongwei Zhang; Yuanzhe Xing; Quan Quan; Zhikun She,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24955v1,https://arxiv.org/pdf/2512.24955v1,arxiv,,"Achieving provable stability in model-free reinforcement learning (RL) remains a challenge, particularly in balancing exploration with rigorous safety. This article introduces MSACL, a framework that integrates exponential stability theory with maximum entropy RL through multi-step Lyapunov certific"
370,,VIPER: Process-aware Evaluation for Generative Video Reasoning,Yifan Li; Yukai Gu; Yingqian Min; Zikang Liu; Yifan Du,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24952v1,https://arxiv.org/pdf/2512.24952v1,arxiv,,"Recent breakthroughs in video generation have demonstrated an emerging capability termed Chain-of-Frames (CoF) reasoning, where models resolve complex tasks through the generation of continuous frames. While these models show promise for Generative Video Reasoning (GVR), existing evaluation framewor"
371,,Laser intracavity absorption magnetometry for optical quantum sensing,J. M. Wollenberg; F. Perona; A. Palaci; H. Wenzel; H. Christopher,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24951v1,https://arxiv.org/pdf/2512.24951v1,arxiv,,"Intracavity absorption spectroscopy (ICAS) is a well-established technique for detecting weak absorption signals with ultrahigh sensitivity. Here, we extend this concept to magnetometry using nitrogen-vacancy (NV) centers in diamond. We introduce laser intracavity absorption magnetometry (LICAM), a "
372,,ProDM: Synthetic Reality-driven Property-aware Progressive Diffusion Model for Coronary Calcium Motion Correction in Non-gated Chest CT,Xinran Gong; Gorkem Durak; Halil Ertugrul Aktas; Vedat Cicek; Jinkui Hao,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24948v1,https://arxiv.org/pdf/2512.24948v1,arxiv,,"Coronary artery calcium (CAC) scoring from chest CT is a well-established tool to stratify and refine clinical cardiovascular disease risk estimation. CAC quantification relies on the accurate delineation of calcified lesions, but is oftentimes affected by artifacts introduced by cardiac and respira"
373,,CPJ: Explainable Agricultural Pest Diagnosis via Caption-Prompt-Judge with LLM-Judged Refinement,Wentao Zhang; Tao Fang; Lina Lu; Lifei Wang; Weihe Zhong,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24947v1,https://arxiv.org/pdf/2512.24947v1,arxiv,,"Accurate and interpretable crop disease diagnosis is essential for agricultural decision-making, yet existing methods often rely on costly supervised fine-tuning and perform poorly under domain shifts. We propose Caption--Prompt--Judge (CPJ), a training-free few-shot framework that enhances Agri-Pes"
374,,HaineiFRDM: Explore Diffusion to Restore Defects in Fast-Movement Films,Rongji Xun; Junjie Yuan; Zhongjie Wang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24946v1,https://arxiv.org/pdf/2512.24946v1,arxiv,,"Existing open-source film restoration methods show limited performance compared to commercial methods due to training with low-quality synthetic data and employing noisy optical flows. In addition, high-resolution films have not been explored by the open-source methods.We propose HaineiFRDM(Film Res"
375,,Dynamic response phenotypes and model discrimination in systems and synthetic biology,Eduardo D. Sontag,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24945v1,https://arxiv.org/pdf/2512.24945v1,arxiv,,"Biological systems encode function not primarily in steady states, but in the structure of transient responses elicited by time-varying stimuli. Overshoots, biphasic dynamics, adaptation kinetics, fold-change detection, entrainment, and cumulative exposure effects often determine phenotypic outcomes"
376,,Interaction of a Vortex Pair with a Polymeric Fluid Layer,Rabia Sonmez; Robert A. Handler; David B. Goldstein; Anton Burstev; Ryan Kelly,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24944v1,https://arxiv.org/pdf/2512.24944v1,arxiv,,"The interaction of vortical structures with boundaries has been extensively studied in Newtonian fluids, where conditions such as no slip walls, free surfaces, or contaminated surfaces dictate whether vortices rebound, dissipate, or generate secondary structures. In this work, we investigate a relat"
377,,RAIR: A Rule-Aware Benchmark Uniting Challenging Long-Tail and Visual Salience Subset for E-commerce Relevance Assessment,Chenji Lu; Zhuo Chen; Hui Zhao; Zhenyi Wang; Pengjie Wang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24943v1,https://arxiv.org/pdf/2512.24943v1,arxiv,,"Search relevance plays a central role in web e-commerce. While large language models (LLMs) have shown significant results on relevance task, existing benchmarks lack sufficient complexity for comprehensive model assessment, resulting in an absence of standardized relevance evaluation metrics across"
378,,Iterative Deployment Improves Planning Skills in LLMs,Augusto B. Corrêa; Yoav Gelberg; Luckeciano C. Melo; Ilia Shumailov; André G. Pereira,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24940v1,https://arxiv.org/pdf/2512.24940v1,arxiv,,"We show that iterative deployment of large language models (LLMs), each fine-tuned on data carefully curated by users from the previous models' deployment, can significantly change the properties of the resultant models. By testing this mechanism on various planning domains, we observe substantial i"
379,,"Vibe Coding, Interface Flattening",Hongrui Jin,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24939v1,https://arxiv.org/pdf/2512.24939v1,arxiv,,"Large language models are reshaping programming by enabling 'vibe coding': the development of softwares through natural-language interaction with model-driven toolchains. This article argues that vibe coding is best understood as interface flattening, a reconfiguration in which previously distinct m"
380,,Modelling the movements of organisms by stochastic theory in a comoving frame,Norberto Lucero Azuara; Rainer Klages,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24937v1,https://arxiv.org/pdf/2512.24937v1,arxiv,,Imagine you walk in a plane. You move by making a step of a certain length per time interval in a chosen direction. Repeating this process by randomly sampling step length and turning angle defines a two-dimensional random walk in what we call comoving frame coordinates. This is precisely how Ross a
381,,Searching for Periodicity in FRB 20240114A,J. I. Katz,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24936v1,https://arxiv.org/pdf/2512.24936v1,arxiv,,"FRB 20240114A is extraordinarily active, and therefore presents an opportunity to search for the periodicity predicted by magnetar models of Fast Radio Bursts (FRB). Zhang, et al. (2025) observed 11,553 bursts, including 3196 on MJD 60381 (March 12, 2024). We find no significant peak in the periodog"
382,,Fair Committee Selection under Ordinal Preferences and Limited Cardinal Information,Ameet Gadekar; Aristides Gionis; Suhas Thejaswi; Sijing Tu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24934v1,https://arxiv.org/pdf/2512.24934v1,arxiv,,"We study the problem of fair $k$-committee selection under an egalitarian objective. Given $n$ agents partitioned into $m$ groups (\eg, demographic quotas), the goal is to aggregate their preferences to form a committee of size $k$ that guarantees minimum representation from each group while minimiz"
383,,Adaptive Dependency-aware Prompt Optimization Framework for Multi-Step LLM Pipeline,Minjun Zhao; Xinyu Zhang; Shuai Zhang; Deyang Li; Ruifeng Shi,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24933v1,https://arxiv.org/pdf/2512.24933v1,arxiv,,"Multi-step LLM pipelines invoke large language models multiple times in a structured sequence and can effectively solve complex tasks, but their performance heavily depends on the prompts used at each step. Jointly optimizing these prompts is difficult due to missing step-level supervision and inter"
384,,Constraints on the perfect phylogeny mixture model and their effect on reducing degeneracy,John Marangola; Azadeh Sheikholeslami; José Bento,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24930v1,https://arxiv.org/pdf/2512.24930v1,arxiv,,"The perfect phylogeny mixture (PPM) model is useful due to its simplicity and applicability in scenarios where mutations can be assumed to accumulate monotonically over time. It is the underlying model in many tools that have been used, for example, to infer phylogenetic trees for tumor evolution an"
385,,Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach,Yuchen Jiao; Na Li; Changxiao Cai; Gen Li,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24927v1,https://arxiv.org/pdf/2512.24927v1,arxiv,,"Higher-order ODE solvers have become a standard tool for accelerating diffusion probabilistic model (DPM) sampling, motivating the widespread view that first-order methods are inherently slower and that increasing discretization order is the primary path to faster generation. This paper challenges t"
386,,Towards Provably Secure Generative AI: Reliable Consensus Sampling,Yu Cui; Hang Fu; Sicheng Pan; Zhuoyu Sun; Yifei Liu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24925v1,https://arxiv.org/pdf/2512.24925v1,arxiv,,Existing research on generative AI security is primarily driven by mutually reinforcing attack and defense methodologies grounded in empirical experience. This dynamic frequently gives rise to previously unknown attacks that can circumvent current detection and prevention. This necessitates the cont
387,,Semi-Supervised Diversity-Aware Domain Adaptation for 3D Object detection,Bartłomiej Olber; Jakub Winter; Paweł Wawrzyński; Andrii Gamalii; Daniel Górniak,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24922v1,https://arxiv.org/pdf/2512.24922v1,arxiv,,"3D object detectors are fundamental components of perception systems in autonomous vehicles. While these detectors achieve remarkable performance on standard autonomous driving benchmarks, they often struggle to generalize across different domains - for instance, a model trained in the U.S. may perf"
388,,"No Vision, No Wearables: 5G-based 2D Human Pose Recognition with Integrated Sensing and Communications",Haojin Li; Dongzhe Li; Anbang Zhang; Wenqi Zhang; Chen Sun,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24923v1,https://arxiv.org/pdf/2512.24923v1,arxiv,,"With the increasing maturity of contactless human pose recognition (HPR) technology, indoor interactive applications have raised higher demands for natural, controller-free interaction methods. However, current mainstream HPR solutions relying on vision or radio-frequency (RF) (including WiFi, radar"
389,,Valence quark distribution of the pion inside a medium with finite baryon density: A Nambu--Jona-Lasinio model approach,Ashutosh Dwibedi; Satyajit Puhan; Sabyasachi Ghosh; Harleen Dahiya,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24921v1,https://arxiv.org/pdf/2512.24921v1,arxiv,,We calculate the in-medium valence quark distribution of the pion immersed in a finite baryon density using the light-cone quark model. The medium-modified pion properties are obtained by using the constituent quark mass-dependent light cone wave functions. To obtain the constituent quark masses at 
390,,Cosmological dynamics and observational constraints of an interacting early scalar field coupled to radiation,Dorian Araya; Felipe Herrera; Nelson Videla,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24918v1,https://arxiv.org/pdf/2512.24918v1,arxiv,,"We study the cosmic evolution of an interacting scalar field radiation model, in which a minimally coupled scalar field exchanges energy with the radiation sector through an exponential coupling. Extending previous formulations, a non-relativistic matter component is included explicitly, which allow"
391,,Frequent subgraph-based persistent homology for graph classification,Xinyang Chen; Amaël Broustet; Guoting Chen,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24917v1,https://arxiv.org/pdf/2512.24917v1,arxiv,,"Persistent homology (PH) has recently emerged as a powerful tool for extracting topological features. Integrating PH into machine learning and deep learning models enhances topology awareness and interpretability. However, most PH methods on graphs rely on a limited set of filtrations, such as degre"
392,,"Existence, uniqueness, and approximability of solutions to the classical Melan equation in suspension bridges",Jinxiang Wang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24915v1,https://arxiv.org/pdf/2512.24915v1,arxiv,,"The classical Melan equation modeling suspension bridges is considered. We first study the explicit expression and the uniform positivity of the analytical solution for the simplified ``less stiff'' model, based on which we develop a monotone iterative technique of lower and upper solutions to inves"
393,,A Liouville-Weierstrass correspondence for Spacelike and Timelike Minimal Surfaces in $\mathbb{L}^3$,Adriana A. Cintra; Iury Domingos; Irene I. Onnis,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24908v1,https://arxiv.org/pdf/2512.24908v1,arxiv,,"We investigate a correspondence between solutions $λ(x,y)$ of the Liouville equation \[ Δλ= -\varepsilon e^{-4λ}, \] and the Weierstrass representations of spacelike ($\varepsilon = 1$) and timelike ($\varepsilon = -1$) minimal surfaces with diagonalizable Weingarten map in the three-dimensional Lor"
394,,Stochastic factors can matter: improving robust growth under ergodicity,Balint Binkert; David Itkin; Paul Mangers Bastian; Josef Teichmann,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24906v1,https://arxiv.org/pdf/2512.24906v1,arxiv,,"Drifts of asset returns are notoriously difficult to model accurately and, yet, trading strategies obtained from portfolio optimization are very sensitive to them. To mitigate this well-known phenomenon we study robust growth-optimization in a high-dimensional incomplete market under drift uncertain"
395,,One-Shot Camera-Based Extrusion Optimization for High Speed Fused Filament Fabrication,Yufan Lin; Xavier Guidetti; Yannick Nagel; Efe C. Balta; John Lygeros,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24905v1,https://arxiv.org/pdf/2512.24905v1,arxiv,,"Off-the-shelf fused filament fabrication 3D printers are widely accessible and convenient, yet they exhibit quality loss at high speeds due to dynamic mis-synchronization between printhead motion and material extrusion systems, notably corner over-extrusion. Existing methods require specialized hard"
396,,"FinMMDocR: Benchmarking Financial Multimodal Reasoning with Scenario Awareness, Document Understanding, and Multi-Step Computation",Zichen Tang; Haihong E; Rongjin Li; Jiacheng Liu; Linwei Jia,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24903v1,https://arxiv.org/pdf/2512.24903v1,arxiv,,"We introduce FinMMDocR, a novel bilingual multimodal benchmark for evaluating multimodal large language models (MLLMs) on real-world financial numerical reasoning. Compared to existing benchmarks, our work delivers three major advancements. (1) Scenario Awareness: 57.9% of 1,200 expert-annotated pro"
397,,Spectral Graph Neural Networks for Cognitive Task Classification in fMRI Connectomes,Debasis Maji; Arghya Banerjee; Debaditya Barman,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24901v1,https://arxiv.org/pdf/2512.24901v1,arxiv,,"Cognitive task classification using machine learning plays a central role in decoding brain states from neuroimaging data. By integrating machine learning with brain network analysis, complex connectivity patterns can be extracted from functional magnetic resonance imaging connectomes. This process "
398,,MTSP-LDP: A Framework for Multi-Task Streaming Data Publication under Local Differential Privacy,Chang Liu; Junzhou Zhao,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24899v1,https://arxiv.org/pdf/2512.24899v1,arxiv,,"The proliferation of streaming data analytics in data-driven applications raises critical privacy concerns, as directly collecting user data may compromise personal privacy. Although existing $w$-event local differential privacy (LDP) mechanisms provide formal guarantees without relying on trusted t"
399,,FusDreamer: Label-Efficient Remote Sensing World Model for Multimodal Data Classification,Jinping Wang; Weiwei Song; Hao Chen; Jinchang Ren; Huimin Zhao,2025,IEEE Transactions on Geoscience and Remote Sensing,,,,,3,0.000,0.000,10.1109/TGRS.2025.3554862,https://www.semanticscholar.org/paper/dfd61809de740483cc1fe5e75ac5772ef0d0dd6a,,semantic_scholar,,"World models significantly enhance hierarchical understanding, improving data integration and learning efficiency. To explore the potential of the world model in the remote sensing (RS) field, this article proposes a label-efficient RS world model for multimodal data fusion (FusDreamer). The FusDrea"
400,,"Abstract 189: Developing a patient-derived organoid biobank, suitable for large scale drug screenings",L. Fielmich; Annemarie Buijs; Daniele Mori; Bastiaan J. Viergever; N. Draoui,2023,Cancer Research,,,,,1,0.000,0.000,10.1158/1538-7445.am2023-189,https://www.semanticscholar.org/paper/0aafd52701190cec84177be30540ddd816fba645,,semantic_scholar,,"
 Conventional models for preclinical drug screening offer poor predictive value for patient response, causing high attrition rates of new agents in the clinic. HUB’s proprietary Patient-Derived Organoid (PDO) Technology enables long-term expansion of primary patient material to generate ‘mini organ"
401,,Robust and Controllable Object-Centric Learning through Energy-based Models,Ruixiang Zhang; Tong Che; B. Ivanovic; Renhao Wang; M. Pavone,2022,International Conference on Learning Representations,,,,,9,0.000,0.000,10.48550/arXiv.2210.05519,https://www.semanticscholar.org/paper/81f5859549221ecf9f42262b8c13e68d68b0a9a1,http://arxiv.org/pdf/2210.05519,semantic_scholar,,"Humans are remarkably good at understanding and reasoning about complex visual scenes. The capability to decompose low-level observations into discrete objects allows us to build a grounded abstract representation and identify the compositional structure of the world. Accordingly, it is a crucial st"
402,,DisMo: Disentangled Motion Representations for Open-World Motion Transfer,Thomas Ressler-Antal; Frank Fundel; Malek Ben Alaya; Stefan Andreas Baumann; Felix Krause,2025,,,,,,0,0.000,0.000,,https://www.semanticscholar.org/paper/41803992a1ddf639c785b46514a3f151962a35a7,,semantic_scholar,,"Recent advances in text-to-video (T2V) and image-to-video (I2V) models, have enabled the creation of visually compelling and dynamic videos from simple textual descriptions or initial frames. However, these models often fail to provide an explicit representation of motion separate from content, limi"
403,,French Dance in the New World: Fanny Elssler’s American Fans,Madison Mainwaring,2025,Dix-Neuf,,,,,0,0.000,0.000,10.1080/14787318.2025.2522559,https://www.semanticscholar.org/paper/20ac12ffaee3042b5ca638c053d4e1e120e49976,,semantic_scholar,,"ABSTRACT When ballerina Fanny Elssler broke her contract with the Paris Opera in 1841 to extend her tour in the US, she made headlines on both sides of the Atlantic. Parisian critics argued that an uncultured American public could not appreciate her art. Their American counterparts responded by sayi"
404,,Optimization of the World Ocean Model of Biogeochemistry and Trophic dynamics (WOMBAT) using surrogate machine learning methods,Pearse J. Buchanan; P. J. Reddy; Richard J. Matear; M. Chamberlain; Tyler Rohr,2025,Biogeosciences,,,,,0,0.000,0.000,10.5194/bg-22-5349-2025,https://www.semanticscholar.org/paper/4ce48bb0bbd0f4506ad8aa77a98b8d8792432d0f,,semantic_scholar,,"Abstract. The introduction of new processes in biogeochemical models brings new model parameters that must be set. Optimization of the model parameters is crucial to ensure that model performance is based on process representation (i.e., functional forms) rather than poor choices of input parameter "
405,,Seasonal extrema of sea surface temperature in CMIP6 models,Yanxin Wang; K. Heywood; D. Stevens; G. Damerell,2021,Ocean Science (OS),,,,,24,0.000,0.000,10.1002/essoar.10505918.1,https://www.semanticscholar.org/paper/a18447e1791838071af76d61f9bf3dcb3cb5208f,https://doi.org/10.1002/essoar.10505918.1,semantic_scholar,,Abstract. CMIP6 model sea surface temperature (SST) seasonal extrema averaged over 1981–2010 are assessed against the World Ocean Atlas (WOA18) observational climatology. We propose a mask to identify and exclude regions of large differences between three commonly-used climatologies. The biases in S
406,,Intuitive physics understanding emerges from self-supervised pretraining on natural videos,Q. Garrido; Nicolas Ballas; Mahmoud Assran; Adrien Bardes; Laurent Najman,2025,arXiv.org,,,,,29,0.000,0.000,10.48550/arXiv.2502.11831,https://www.semanticscholar.org/paper/c5e7e68a6214f5f2726b5d1845968e5f93fcef1c,,semantic_scholar,,"We investigate the emergence of intuitive physics understanding in general-purpose deep neural network models trained to predict masked regions in natural videos. Leveraging the violation-of-expectation framework, we find that video prediction models trained to predict outcomes in a learned represen"
407,,Probabilistic voting models with varying speeds of Correlation decay,G. Toth,2022,Advances in Applied Probability,,,,,0,0.000,0.000,10.1017/apr.2024.18,https://www.semanticscholar.org/paper/22981484c99d3c4d0e732e4d331e1a177e3da8e4,,semantic_scholar,,Abstract We model voting behaviour in the multi-group setting of a two-tier voting system using sequences of de Finetti measures. Our model is defined by using the de Finetti representation of a probability measure (i.e. as a mixture of conditionally independent probability measures) describing voti
408,,National Representation without Citizenship: the Special Case of Rugby,Danyel Reiche,2021,,,,,,2,0.000,0.000,10.2478/pce-2021-0021,https://www.semanticscholar.org/paper/860baa8c0e04e1b3ed898e9021c76aa0f129f23c,https://doi.org/10.2478/pce-2021-0021,semantic_scholar,,"Abstract This article is a case study of one of the few sports, rugby, that does not link national representation exclusively to citizenship. It discusses who may represent a country in major events and under which conditions. It analyses the consequences of the rules on different stakeholders; and "
409,,Deep Representation Learning for Vietnamese Speaker Recognition,Cao Truong Tran; Dinh Tan Nguyen; Ho Tan Hoang,2021,International Conference on Knowledge and Systems Engineering,,,,,0,0.000,0.000,10.1109/KSE53942.2021.9648808,https://www.semanticscholar.org/paper/e8168aaff97a397b57273b866b088ac9c7135fdf,,semantic_scholar,,"Speaker recognition is the process of identifying an individual from their voices, and it has been widely applied in many real-world applications. Recently, deep learning has instigated a revolutionary high success rate in speaker recognition. The major advantage of deep learning over conventional m"
410,,Optimization modeling and verification from problem specifications using a multi-agent multi-stage LLM framework,Mahdi Mostajabdaveh; Timothy T. L. Yu; Rindranirina Ramamonjison; G. Carenini; Zirui Zhou,2024,INFOR. Information systems and operational research,,,,,21,0.000,0.000,10.1080/03155986.2024.2381306,https://www.semanticscholar.org/paper/ba9437c571310ef5dd84820daea87122a395b83b,,semantic_scholar,,Abstract This paper explores the use of Large Language Models (LLMs) in modeling real-world optimization problems. We concretely define the task of translating natural language descriptions into optimization models (NL2OPT) and provide criteria for classifying optimization problems for the NL2OPT ta
411,,"Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations",Magdalena Uber; M. Haller; C. Brendel; G. Hillebrand; T. Hoffmann,2024,Hydrology and Earth System Sciences,,,,,18,0.000,0.000,10.5194/hess-28-87-2024,https://www.semanticscholar.org/paper/ada27d81b3f475e3dcd4bf765290af347b1db0fd,https://hess.copernicus.org/articles/28/87/2024/hess-28-87-2024.pdf,semantic_scholar,,"Abstract. Heavy rainfall is the main driver of soil erosion by water, which is a threat to soil and water resources across the globe. As a consequence of climate change, precipitation – especially extreme precipitation – is increasing in a warmer world, leading to an increase in rainfall erosivity. "
412,,Synthetic users: insights from designers’ interactions with persona-based chatbots,(Eric) Heng Gu; Senthil K. Chandrasegaran; Peter Lloyd,2025,"Artificial intelligence for engineering design, analysis and manufacturing",,,,,5,0.000,0.000,10.1017/S0890060424000283,https://www.semanticscholar.org/paper/f1d926623e2dc7c5ffcdf4d88ca7d658e82d0225,,semantic_scholar,,"Abstract Personas are hypothetical representations of real-world people used as storytelling tools to help designers identify the goals, constraints, and scenarios of particular user groups. A well-constructed persona can provide enough detail to trigger recognition and empathy while leaving room fo"
413,,Physically based modelling of glacier evolution under climate change in the tropical Andes,J. Mackay; N. Barrand; D. Hannah; E. Potter; Nilton Montoya,2025,The Cryosphere,,,,,4,0.000,0.000,10.5194/tc-19-685-2025,https://www.semanticscholar.org/paper/6a6923d804f740e9aa960e42c516a0c79f227282,https://doi.org/10.5194/tc-19-685-2025,semantic_scholar,,"Abstract. In recent years, opportunities have opened up to develop and validate glacier models in regions that have previously been infeasible due to observation and/or computational constraints thanks to the availability of globally capable glacier evolution modelling codes and spatially extensive "
414,,Neural Causal Abstractions,K. Xia; E. Bareinboim,2024,AAAI Conference on Artificial Intelligence,,,,,13,0.000,0.000,10.48550/arXiv.2401.02602,https://www.semanticscholar.org/paper/6f0eef06670ccf10d525f58c43ef660a914b3bee,,semantic_scholar,,"The ability of humans to understand the world in terms of cause and effect relationships, as well as their ability to compress information into abstract concepts, are two hallmark features of human intelligence. These two topics have been studied in tandem under the theory of causal abstractions, bu"
415,,Disentangling Representations through Multi-task Learning,Pantelis Vafidis; Aman Bhargava; Antonio Rangel,2024,International Conference on Learning Representations,,,,,4,0.000,0.000,,https://www.semanticscholar.org/paper/48da03a16e49f1dad15918743f65a26787f45bbc,,semantic_scholar,,"Intelligent perception and interaction with the world hinges on internal representations that capture its underlying structure (''disentangled'' or ''abstract'' representations). Disentangled representations serve as world models, isolating latent factors of variation in the world along approximatel"
416,,Traffic Scene-Informed Attribution of Autonomous Driving Decisions,Rui Shi; Tianxing Li; Yasushi Yamaguchi; Liguo Zhang,2025,IEEE transactions on intelligent transportation systems (Print),,,,,3,0.000,0.000,10.1109/TITS.2025.3547879,https://www.semanticscholar.org/paper/80e7fc7ab85928c023e781738b80f5f7dd93d6d4,,semantic_scholar,,"Deep neural networks (DNNs) have advanced autonomous driving, but their lack of transparency remains a major obstacle to real-world application. Attribution methods, which aim to explain DNN decisions, offer a potential solution. However, existing methods, primarily designed for image classification"
417,,Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills,Tianhao Wei; Liqian Ma; Rui Chen; Weiye Zhao; Changliu Liu,2024,Conference on Robot Learning,,,,,8,0.000,0.000,10.48550/arXiv.2405.11380,https://www.semanticscholar.org/paper/39484c454bde6b96d013873f7300481473e993b4,,semantic_scholar,,"The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require avoidance of certain regions, while others require convergence to certain states. Satisfying these varied requirements wit"
418,,HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery,S. Meena; Lorenzo Nava; Kushanav Bhuyan; Silvia Puliero; L. P. Soares,2023,Earth System Science Data,,,,,36,0.000,0.000,10.5194/essd-15-3283-2023,https://www.semanticscholar.org/paper/f2021a75fdd401bcab31e9d7519d3fc8a8619ff9,https://doi.org/10.5194/essd-15-3283-2023,semantic_scholar,,"Abstract. Multiple landslide events occur often across the world which have the
potential to cause significant harm to both human life and property.
Although a substantial amount of research has been conducted to
address mapping of landslides using Earth observation (EO) data, several
gaps and uncer"
419,,Fragmentation and multithreading of experience in the default-mode network,Fahd Yazin; Gargi Majumdar; Neil Bramley; Paul Hoffman,2025,bioRxiv,,,,,3,0.000,0.000,10.1038/s41467-025-63522-y,https://www.semanticscholar.org/paper/b9f0d92c5ec0d00d8d2c5c89d32ea2d481b81417,,semantic_scholar,,"Reliance on internal predictive models of the world is central to many theories of human cognition. Yet it is unknown whether humans acquired multiple separate internal models, each evolved for a specific domain, or maintain a globally unified representation. Using fMRI during naturalistic experienc"
420,,A predictive human model of language challenges traditional views in linguistics and pretrained transformer research,S. Torres-Martínez,2024,Language and Semiotic Studies,,,,,6,0.000,0.000,10.1515/lass-2024-0018,https://www.semanticscholar.org/paper/c48a4f84984e237fd6c1ee606c3fc8cf982c12b2,https://doi.org/10.1515/lass-2024-0018,semantic_scholar,,Abstract This paper introduces a theory of mind that positions language as a cognitive tool in its own right for the optimization of biological fitness. I argue that human language reconstruction of reality results from biological memory and adaptation to uncertain environmental conditions for the r
421,,Causality in Neural Networks - An Extended Abstract,Abbavaram Gowtham Reddy,2021,"AAAI/ACM Conference on AI, Ethics, and Society",,,,,1,0.000,0.000,10.1145/3461702.3462467,https://www.semanticscholar.org/paper/3c96179c244af79829ab266ee5893139c0618a06,https://arxiv.org/pdf/2106.05842,semantic_scholar,,Causal reasoning is the main learning and explanation tool used by humans. AI systems should possess causal reasoning capabilities to be deployed in the real world with trust and reliability. Introducing the ideas of causality to machine learning helps in providing better learning and explainable mo
422,,Student Research Abstract: Continuous-Time Generative Graph Neural Network for Attributed Dynamic Graphs,Alice Moallemy-Oureh,2021,,,,,,1,0.000,0.000,,https://www.semanticscholar.org/paper/1bf3fad6fcce6cb73b31892291b4358662931aa1,,semantic_scholar,,
423,,Visuals of climate change in school textbooks,Mareike Schauss; Eva Nöthen; Marie-Paulina Ottosander; Sandra Sprenger,2024,International Research in Geographical and Environmental Education,,,,,5,0.000,0.000,10.1080/10382046.2023.2298557,https://www.semanticscholar.org/paper/07f07309820d265cbc1a96020aea3805f5401682,,semantic_scholar,,"Abstract With the “pictorial turn”, the picture has gained a new significance as a medium. It is impossible to imagine a digitalized world affected by mass media without pictures. While there are several studies on the impact of pictures in the discourse on climate change in the media, there has bee"
424,,A fractal framework for channel–hillslope coupling,Benjamin Kargère; José Constantine; T. Hales; S. Grieve; Stewart Johnson,2025,Earth Surface Dynamics,,,,,2,0.000,0.000,10.5194/esurf-13-403-2025,https://www.semanticscholar.org/paper/2bb196499269898000556d08af38a8240f96bfb7,,semantic_scholar,,"Abstract. Questions of landscape scale in coupled channel–hillslope landscape evolution have been a significant focus of geomorphological research for decades. Studies to date have suggested a characteristic landscape length that marks the shift from fluvial channels to hillslopes, limiting fluvial "
425,,Representing the War. Early Twentieth Century Maps and Models in the Fonds of the Italian War History Museum in Rovereto,Elena Dai Prá; Valentina De Santi; Giannantonio Scaglione,2021,Proceedings of the ICA,,,,,0,0.000,0.000,10.5194/ica-proc-4-23-2021,https://www.semanticscholar.org/paper/841263482dfa58e0e2e0fb2addfd3c8187ec4238,https://www.proc-int-cartogr-assoc.net/4/23/2021/ica-proc-4-23-2021.pdf,semantic_scholar,,"Abstract. The representation of the areas in which some of the most significant events of the First World War took place has produced a wide range of materials, such as cartography, aerial and terrestrial photos, textual descriptions and field surveys. In addition, war events were also represented t"
426,,"Modelling 3-Dimensional cadastral boundaries in a BIM environment: a case study using volumetric format plans in Queensland, Australia",Ben Bryant; Armin Agha Karimi; B. Atazadeh; Abbas Rajabifard,2025,International Journal of Digital Earth,,,,,1,0.000,0.000,10.1080/17538947.2025.2518578,https://www.semanticscholar.org/paper/6600e3cb435191d4d522f7fc5a3ef064ab49c777,,semantic_scholar,,"ABSTRACT The future vision for cadastre in many jurisdictions is to deliver a digital representation of legal and physical dimensions of the real world that is survey accurate, 3D, and dynamic. In Queensland, 3D cadastral plans are represented as Building Format plans and Volumetric Format plans. 3D"
427,,Indian Classical Music Recognition using Deep Convolution Neural Network,S. Aswale; Dr. Prabhat Chandra Shrivastava; Dr. Ratnesh Ranjan; Seema Shende,2024,International journal of electrical and electronics research,,,,,3,0.000,0.000,10.37391/10.37391/ijeer.120112,https://www.semanticscholar.org/paper/50cbd568c8bff216b6ba04694c2ae16843284d8b,https://ijeer.forexjournal.co.in/papers-pdf/ijeer-120112.pdf,semantic_scholar,,A divine approach to communicate feelings about the world occurs through music. There is a huge variety in the language of music. One of the principal variables of Indian social legacy is classical music. Hindustani and Carnatic are the two primary subgenres of Indian classical music. Models have be
428,,METAMORPHOSIS: A DIGITAL APPROACH TO TRANSFORMING COMMUNITIES THROUGH PHOTOGRAMMETRY AND METAVERSE,N. Abramov; H. Lankegowda; S. Liu; L. Barazzetti; C. Beltracchi,2024,"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",,,,,2,0.000,0.000,10.5194/isprs-archives-xlviii-2-w4-2024-1-2024,https://www.semanticscholar.org/paper/a4e081e927e9d5ea8e2168118347ff86d18b4256,https://isprs-archives.copernicus.org/articles/XLVIII-2-W4-2024/1/2024/isprs-archives-XLVIII-2-W4-2024-1-2024.pdf,semantic_scholar,,"Abstract. This research employs a digital strategy to counter rural population decline and urban migration by integrating drone photogrammetry, metaverse, and blockchain technology. The focus is creating detailed 3D models of the settlements, which are subsequently optimized for metaverse platforms "
429,,An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin,J. Redemann; R. Wood; P. Zuidema; S. Doherty; B. Luna,2021,,,,,,176,0.000,0.000,10.5194/ACP-21-1507-2021,https://www.semanticscholar.org/paper/49071db398d449bfd782fb463475f5a9028b0893,https://acp.copernicus.org/articles/21/1507/2021/acp-21-1507-2021.pdf,semantic_scholar,,"Abstract. Southern Africa produces almost a third of the Earth’s biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a five-year NASA"
430,,Bridge and Bound: A Logic-Based Framework for Abstracting (Preliminary Report),Andrzej Szalas,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2510.26654,https://www.semanticscholar.org/paper/6334c745937754745a7f56d3a43f6d815c78c967,,semantic_scholar,,"At its core, abstraction is the process of generalizing from specific instances to broader concepts or models, with the primary objective of reducing complexity while preserving properties essential to the intended purpose. It is a fundamental, often implicit, principle that structures the understan"
431,,A Comparative Analysis of Automatic Speech Recognition Errors in Small Group Classroom Discourse,Jie Cao; Ananya Ganesh; Jon Z. Cai; Rosy Southwell; E. M. Perkoff,2023,"User Modeling, Adaptation, and Personalization",,,,,29,0.000,0.000,10.1145/3565472.3595606,https://www.semanticscholar.org/paper/1b0378d52d8988ffd5ecfb507e23420985171306,https://dl.acm.org/doi/pdf/10.1145/3565472.3595606,semantic_scholar,,"In collaborative learning environments, effective intelligent learning systems need to accurately analyze and understand the collaborative discourse between learners (i.e., group modeling) to provide adaptive support. We investigate how automatic speech recognition (ASR) errors influence discourse m"
432,,Enhanced dual-channel feature fusion approach for rolling bearing fault diagnosis,Jiaxin Wen; Yuqiao Zheng; Yongfei Zhang; Weilong Yu,2025,Nondestructive Testing and Evaluation,,,,,1,0.000,0.000,10.1080/10589759.2025.2507761,https://www.semanticscholar.org/paper/ec7aac5df77d1692c33b0825800e5097e04b38bc,,semantic_scholar,,"ABSTRACT Bearing fault diagnosis models predominantly rely on vibration signals for signal processing. The presence of noise interference and limited feature extraction capacity significantly impedes effective feature representation and compromises model generalisation, consequently leading to subop"
433,,Another kind of authenticity: the visual simulacra of artificial intelligence,Shan Jiang; Kanghua Li,2025,Digital Creativity,,,,,1,0.000,0.000,10.1080/14626268.2025.2467087,https://www.semanticscholar.org/paper/1fa79c6858cda24b7bd24664acc5862fcbdd9b18,,semantic_scholar,,"ABSTRACT The rapid proliferation of visual simulacra generated by artificial intelligence (AI) necessitates a critical examination of their authenticity. This study investigates the authenticity of these simulacra by establishing a framework for evaluation, drawing on imitation theory and the theory"
434,,Learning with Category-Equivariant Representations for Human Activity Recognition,Yoshihiro Maruyama,2025,arXiv.org,,,,,1,0.000,0.000,10.48550/arXiv.2511.00900,https://www.semanticscholar.org/paper/4a36cca58a8e7cce2247bc1514168971d549e463,,semantic_scholar,,"Human activity recognition is challenging because sensor signals shift with context, motion, and environment; effective models must therefore remain stable as the world around them changes. We introduce a categorical symmetry-aware learning framework that captures how signals vary over time, scale, "
435,,"Think Small, Plan Smart: Minimalist Symbolic Abstraction and Heuristic Subspace Search for LLM-Guided Task Planning",Junfeng Tang; Yuping Yan; Zihan Ye; Zhenshou; Song,2025,,,,,,1,0.000,0.000,,https://www.semanticscholar.org/paper/6fccd056e256049ceadbc2300fb68b5446a07370,,semantic_scholar,,"Reliable task planning is pivotal for achieving long-horizon autonomy in real-world robotic systems. Large language models (LLMs) offer a promising interface for translating complex and ambiguous natural language instructions into actionable plans. However, their probabilistic and opaque nature ofte"
436,,Using drawings and deep neural networks to characterize the building blocks of human visual similarity,Kushin Mukherjee; Timothy T. Rogers,2024,Memory & Cognition,,,,,3,0.000,0.000,10.3758/s13421-024-01580-1,https://www.semanticscholar.org/paper/f3c7b30b2165c7f80cddc6ea458bb31b8efaac57,,semantic_scholar,,
437,,Implementation of the dual quaternion algorithm for 3D similarity-based coordinate transformation between Ghana’s local geodetic datum and WGS84,Yao Yevenyo Ziggah; S. Mantey; P. Laari,2024,Reports on Geodesy and Geoinformatics,,,,,1,0.000,0.000,10.2478/rgg-2024-0021,https://www.semanticscholar.org/paper/8295bc80e1ad71dfe3d5e4aa698d49cd21fd8657,,semantic_scholar,,Abstract Modern surveying practice has embraced the use of Global Navigation Satellite System (GNSS) technology due to its attainable precision and uncomplicated functionality. The adoption of this technology has therefore necessitated the transformation of coordinates between satellite-based and cl
438,,Approaching the world of non-human experience: Unnatural ways of worldmaking in Ian McEwan’s fiction,Shang Biwu,2022,Frontiers of Narrative Studies,,,,,0,0.000,0.000,10.1515/fns-2022-2013,https://www.semanticscholar.org/paper/8213e7710b52c502987cfeef502f1cf7da47fa76,,semantic_scholar,,"Abstract The past two decades witnessed an increasing interest in literary worldmaking. This paper begins with examining the current models of worldmaking, in particular, the model of the phenomenological, the constructive, the cognitive psychological, the media, the narratological, and the ethical."
439,,Italy’s Catholic partisan: history and narrative,Alessandro Santagata,2025,Modern Italy,,,,,0,0.000,0.000,10.1017/mit.2024.74,https://www.semanticscholar.org/paper/893e00bb09f60ceebea0e233be8c021c0779733a,,semantic_scholar,,"Abstract This article reviews the evolution of the representation of Italy’s ‘Catholic partisan’. In essence, this involved adaptation of the model of the Catholic soldier, who was able to kill out of love and ‘without hatred’, to the context of a civil war. With particular reference to the case of "
440,,New implementation of data standards for AI in oncology: Experience from the EuCanImage project,Teresa García-Lezana; Maciej Bobowicz; S. Frid; Michael Rutherford; Mikel Recuero,2025,GigaScience,,,,,0,0.000,0.000,10.1093/gigascience/giae101,https://www.semanticscholar.org/paper/634ee00f5dee42eb66944afc61660b3d57c7820f,,semantic_scholar,,"Abstract Background An unprecedented amount of personal health data, with the potential to revolutionize precision medicine, is generated at health care institutions worldwide. The exploitation of such data using artificial intelligence (AI) relies on the ability to combine heterogeneous, multicentr"
441,,Brain-Language Model Alignment: Insights into the Platonic Hypothesis and Intermediate-Layer Advantage,Ángela López-Cardona; Sebastian Idesis; Mireia Masias Bruns; Sergi Abadal; Ioannis Arapakis,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2510.17833,https://www.semanticscholar.org/paper/2e1860bd58710ee6efca9ebe985e58b84260336c,,semantic_scholar,,"Do brains and language models converge toward the same internal representations of the world? Recent years have seen a rise in studies of neural activations and model alignment. In this work, we review 25 fMRI-based studies published between 2023 and 2025 and explicitly confront their findings with "
442,,"Redefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerations",Umashankar Samal; Ajay Mahaputra Kumar,2023,Quality Engineering,,,,,17,0.000,0.000,10.1080/08982112.2023.2241067,https://www.semanticscholar.org/paper/ebc95a334bfc9ba285bb54126ab378d8f2024eac,,semantic_scholar,,"Abstract Software reliability is a critical aspect of ensuring the quality and dependability of software systems. However, existing software reliability models often make assumptions that do not align with real-world scenarios, such as perfect fault removal and independent faults. In this paper, we "
443,,How horror films constructs Blackness: examples of White supremacist media’s enforcement of necropolitics in genre film,L. B. Bailey,2024,Feminist Media Studies,,,,,0,0.000,0.000,10.1080/14680777.2024.2358098,https://www.semanticscholar.org/paper/297a10bedb16b01e3a97425d1d67c28ca2367f0c,,semantic_scholar,,"ABSTRACT Recently, there has been in uptick in Black horror in the horror genre, such as Jordan Peele’s Get Out, US, or HBO’s Lovecraft Country. Despite the recent growth of Black horror, many horror films continue depend on film technologies that contribute to oppression. The necropolitics of the h"
444,,Physics-Constrained Production Forecasting with Direct Fracture Characterization by Field Data,Ziming Xu; Juliana Y. Leung,2025,SPE Annual Technical Conference and Exhibition,,,,,0,0.000,0.000,10.2118/228139-ms,https://www.semanticscholar.org/paper/35d346e01edbaae94a3fc1c99919f4783dabfc35,,semantic_scholar,,"
 Fractured reservoir simulations often rely on abstract fracture parameters—such as length, height, and width—that are difficult to validate with direct measurements, introducing biases in production forecasting. This research presents Assimilation Neural Network (AssimNet), a hybrid data-driven an"
445,,Rank Reversal Mitigation for Enhanced Transition Boundary Discernment in a Bespoke AI System,Steve Chan; Bob Griffin,2025,2025 IEEE World AI IoT Congress (AIIoT),,,,,0,0.000,0.000,10.1109/AIIoT65859.2025.11105272,https://www.semanticscholar.org/paper/d9dadc2dcd86be67fefa8b36535d1c8dc04474ff,,semantic_scholar,,"The challenge of representation variability for abstract concepts, such as ""entrepreneurship,"" and the sorting/ranking of the involved precursor notions and attributes has persisted even amidst the advent of Large Concept Models (LCMs). To accommodate Real World Scenario (RWS) applications (e.g., en"
446,,Enriching Pre-Training Using Fuzzy Logic,Vansh Gupta; Vandana Bharti; Abhinav Kumar; Anshul Sharma; Sanjay Kumar Singh,2025,IEEE International Conference on Fuzzy Systems,,,,,0,0.000,0.000,10.1109/FUZZ62266.2025.11152046,https://www.semanticscholar.org/paper/6945e4834b5282a1c5f12d9ff40409297a4d6a89,,semantic_scholar,,Graph representation learning advances graph machine learning by encoding structural and relational information into feature vectors. This study introduces a fuzzy logic-based pre-processing layer that enhances node representations by adding semantic diversity and contextual understanding. The layer
447,,Goal-VLA: Image-Generative VLMs as Object-Centric World Models Empowering Zero-shot Robot Manipulation,Haonan Chen; Jingxiang Guo; Bangjun Wang; Tianrui Zhang; Xuchuan Huang,2025,,,,,,1,0.000,0.000,,https://www.semanticscholar.org/paper/ffccb1b3247f4e63d1b0c8b8c31c70cb0db16e3d,,semantic_scholar,,"Generalization remains a fundamental challenge in robotic manipulation. To tackle this challenge, recent Vision-Language-Action (VLA) models build policies on top of Vision-Language Models (VLMs), seeking to transfer their open-world semantic knowledge. However, their zero-shot capability lags signi"
448,,Sparse representation learning with modified q-VAE towards minimal realization of world model,Taisuke Kobayashi; Ryoma Watanuki,2022,Adv. Robotics,,,,,7,0.000,0.000,10.1080/01691864.2023.2221715,https://www.semanticscholar.org/paper/cd5baf2998cbd3f8ff584179f9b290ce9a1be6ff,https://arxiv.org/pdf/2208.03936,semantic_scholar,,"Extraction of low-dimensional latent space from high-dimensional observation data is essential to construct a real-time robot controller with a world model on the extracted latent space. However, there is no established method for tuning the dimension size of the latent space automatically, sufferin"
449,,AtResNet: Residual Atrous CNN with Multi-scale Feature Representation for Low Complexity Acoustic Scene Classification,Aswathy Madhu; Suresh Kumaraswamy,2022,"Circuits, systems, and signal processing",,,,,2,0.000,0.000,10.1007/s00034-022-02107-2,https://www.semanticscholar.org/paper/5c0135a85e0cd03693391008e7a1bcfc1538b982,,semantic_scholar,,
450,,"Abstract 2145: Genetic ancestry associations with pancreatic cancer mutational profiles from a diverse 9,274-patient real-world cohort",Brooke Rhead; Vignesh Vudatha; Y. Pouliot; Edward Williamns; A. Riner,2024,Cancer Research,,,,,0,0.000,0.000,10.1158/1538-7445.am2024-2145,https://www.semanticscholar.org/paper/d21d17242525dc6e87699b8f24edea5c052703d3,,semantic_scholar,,"
 Pancreatic cancer is an aggressive malignancy associated with racial/ethnic disparities. Notably, Black patients have a higher incidence and mortality compared to their White counterparts. However, low representation of Black and Hispanic patients in cancer genomics studies hampers our understandi"
451,,HYBRID DEEP LEARNING MODELS FOR MULTILINGUAL SENTIMENT ANALYSIS IN LOW-RESOURCE LANGUAGES,Hendri Purnomo; Randi Estian Pambudi; Danang Ade Muktiawan; Sylvia Sylvia,2025,Coding: Journal of Computing and Software Engineering,,,,,0,0.000,0.000,10.25181/coding.v1i1.4306,https://www.semanticscholar.org/paper/8fe02571bdbc8699903f54cc2ccfdfc52ed2e488,,semantic_scholar,,"Multilingual sentiment analysis poses significant challenges, especially in the context of languages with low resources. The study proposes a hybrid deep learning model based on the CNN-BiLSTM architecture to classify sentiment in multiple languages, including those with limited corpus and lexical r"
452,,"Abstract C043:
 PIN1
 mRNA expression in biliary tract cancer: A multiomic analysis of its prognostic relevance and association with tumor-immune states in a large real-world cohort",Justin H. Lo; Thatcher R Heumann; Denise Shieh; Stamatina Fragkogianni; Brooke Rhead,2025,Molecular Cancer Therapeutics,,,,,0,0.000,0.000,10.1158/1535-7163.targ-25-c043,https://www.semanticscholar.org/paper/aa777000708a4a6f6981d9aa45160715148365a2,,semantic_scholar,,"
 
 
 PIN1, a peptidyl-prolyl isomerase, is overexpressed in many tumor types. Previous studies in pancreatic cancer have shown an association between higher PIN1 expression with an immunosuppressive tumor microenvironment (TME) and poor clinical outcomes. Inhibition of PIN1 in animal models renders"
453,,Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system,M. Mile; S. Guedj; R. Randriamampianina,2024,Geoscientific Model Development,,,,,0,0.000,0.000,10.5194/gmd-17-6571-2024,https://www.semanticscholar.org/paper/7f1e538713569c8334654bd265f3021f606a2311,,semantic_scholar,,"Abstract. The microwave radiances are key observations, especially over data-sparse regions, for operational data assimilation in numerical weather prediction (NWP). An often applied simplification is that these observations are used as point measurements; however, the satellite field of view may co"
454,,Comprehensive Study on Performance Evaluation and Optimization of Model Compression: Bridging Traditional Deep Learning and Large Language Models,Aayush Saxena; Arit Kumar Bishwas; Ayush Ashok Mishra; Ryan Armstrong,2024,arXiv.org,,,,,5,0.000,0.000,10.48550/arXiv.2407.15904,https://www.semanticscholar.org/paper/b5e760c391804e66b610b5753e193eb5c5acf2ba,,semantic_scholar,,"Deep learning models have achieved tremendous success in most of the industries in recent years. The evolution of these models has also led to an increase in the model size and energy requirement, making it difficult to deploy in production on low compute devices. An increase in the number of connec"
455,,A Fast Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation,Yunchang Wang; Yifan Fu; Zebin Wu; Chengxun He; Peng Zheng,2025,IEEE International Geoscience and Remote Sensing Symposium,,,,,0,0.000,0.000,10.1109/IGARSS55030.2025.11243679,https://www.semanticscholar.org/paper/f4306a0caec2823a3f52a6cef1e90c92615d4ef2,,semantic_scholar,,"The low-rank and sparse representation (LRASR) model has emerged as a powerful tool for hyperspectral image anomaly detection in real-world applications. However, the prohibitive computational complexity of large-scale singular value decomposition (SVD) limits the scalability of LRASR, making it inc"
456,,Selecting and weighting dynamical models using data-driven approaches,P. Le Bras; F. Sévellec; P. Tandeo; Juan Ruiz; P. Ailliot,2024,Nonlinear Processes in Geophysics,,,,,2,0.000,0.000,10.5194/npg-31-303-2024,https://www.semanticscholar.org/paper/5463e75fe76900d223892f983a8d12b46ef296f1,,semantic_scholar,,"Abstract. In geosciences, multi-model ensembles are helpful to explore the robustness of a range of results. To obtain a synthetic and improved representation of the studied dynamic system, the models are usually weighted. The simplest method, namely the model democracy, gives equal weights to all m"
457,,Robust auto-weighted and dual-structural representation learning for image clustering,Kun Jiang; Zhaoli Liu; Qindong Sun,2024,J. Electronic Imaging,,,,,1,0.000,0.000,10.1117/1.JEI.33.4.043039,https://www.semanticscholar.org/paper/7700b45f828ce3f9c106f38f79ef5c626ef090a1,,semantic_scholar,,"Abstract. High-dimensional data samples tend to contain highly correlated features and are quite fragile to various noises and outliers in practical applications. For subspace clustering models, it has appeared to be inadequate to adopt conventional norm-based distance measurements to resist feature"
458,,IoT Device Authentication via RAM Trace Analysis: A Representation Learning Framework,Asif Iqbal; M. Aman; Biplab Sikdar,2024,Global Communications Conference,,,,,0,0.000,0.000,10.1109/GLOBECOM52923.2024.10901561,https://www.semanticscholar.org/paper/920cd3e808876d817a3caab7800c8c1c4d39279f,,semantic_scholar,,"Recent advances in IoT, machine learning, and edge computing have driven transformative paradigms like smart cities, grids, healthcare, and transportation systems, providing efficient solutions. This has led to a pervasive proliferation of connected devices, ranging from high-power computers to low-"
459,,ReGA: Representation-Guided Abstraction for Model-based Safeguarding of LLMs,Zeming Wei; Chengcan Wu; Meng Sun,2025,arXiv.org,,,,,3,0.000,0.000,10.48550/arXiv.2506.01770,https://www.semanticscholar.org/paper/dcc59902da1b95f1f63d5f2836327822f94a276a,,semantic_scholar,,"Large Language Models (LLMs) have achieved significant success in various tasks, yet concerns about their safety and security have emerged. In particular, they pose risks in generating harmful content and vulnerability to jailbreaking attacks. To analyze and monitor machine learning models, model-ba"
460,,Low-Rank Sparse Generative Adversarial Unsupervised Domain Adaptation for Multitarget Traffic Scene Semantic Segmentation,M. Saffari; Mahdi Khodayar,2024,IEEE Transactions on Industrial Informatics,,,,,9,0.000,0.000,10.1109/TII.2023.3291402,https://www.semanticscholar.org/paper/3520845cd4900a7f4f9b82771166bd82f9282394,,semantic_scholar,,"Semantic segmentation in diverse real-world traffic scenes is a challenging task for autonomous vehicles to have a reliable understanding of the outside environment. Although deep visual models show a remarkable performance on traffic scene segmentation, they need significant improvements when the s"
461,,SETUP: Sentence-level English-To-Uniform Meaning Representation Parser,Emma Markle; Javier Gutierrez Bach; Shira Wein,2025,,,,,,0,0.000,0.000,,https://www.semanticscholar.org/paper/ff0efe591c06f8be2e5cec944f348dee161ad71e,,semantic_scholar,,"Uniform Meaning Representation (UMR) is a novel graph-based semantic representation which captures the core meaning of a text, with flexibility incorporated into the annotation schema such that the breadth of the world's languages can be annotated (including low-resource languages). While UMR shows "
462,,Recommending Learning Objects through Attentive Heterogeneous Graph Convolution and Operation- Aware Neural Network (Extended Abstract),Yifan Zhu; Qika Lin; Hao Lu; Kaize Shi; Donglei Liu,2024,IEEE International Conference on Data Engineering,,,,,1,0.000,0.000,10.1109/ICDE60146.2024.00505,https://www.semanticscholar.org/paper/15646e51a590f658b99f4267080c2142d5a7a18f,,semantic_scholar,,"Currently, the increasing information overload on Massive Open Online Courses(MOOCs) inhibits the appropriate choice of learning objects by learners, leading to low efficiency and high dropout rates. However, in MOOC platforms, recommendation network structures that can selectively extract implicit "
463,,Iris matching recognition based on information quantity and complex domain in low-computational power scenarios,Shuai Liu,2025,J. Electronic Imaging,,,,,0,0.000,0.000,10.1117/1.JEI.34.5.053044,https://www.semanticscholar.org/paper/7bbf7f2f1f1f65a3ef0153c0e7c3c82e9cd6e6e6,,semantic_scholar,,"Abstract. Iris recognition faces challenges from uncertainties in image acquisition, which limit the effective expression of information. Existing recognition models built on deep learning structures have rigid requirements for high-performance computing resources, restricting their application scop"
464,,Abstract TP171: Automated Large Vessel Occlusions Detection: Improved Diagnostic Accuracy in MCA M2 Segment Using Deep Learning,A. Franciosini; C. Avare; Peter D. Chang; D. Chow; Christopher G Filippi,2025,Stroke,,,,,1,0.000,0.000,10.1161/str.56.suppl_1.tp171,https://www.semanticscholar.org/paper/ffbc835b101ea4c84decae0f4da9f8edab486a5e,,semantic_scholar,,"
 Introduction:
 Integrating AI into clinical practice enables precise diagnosis and could potentially enhance outcomes for patients with large vessel occlusion (LVO). Although advancements in AI have shown promise in enhancing diagnostic accuracy, several studies have reported very low sensitivitie"
465,,A Switched-Capacitor Compute-in-Memory Ising Hardware Annealing Accelerator,Ariane Hannon; Viet Nguyen; R. B. Staszewski,2025,Irish Signals and Systems Conference,,,,,0,0.000,0.000,10.1109/ISSC67739.2025.11291378,https://www.semanticscholar.org/paper/e9c190a7eedc4c090ebe8cee84c16586b3a97f28,,semantic_scholar,,Ising hardware accelerators are needed to efficiently solve the pervasive real-world combinatorial optimisation problems (COPs) that would otherwise be intractable to solve using brute-force approaches on a traditional computer. The Ising model abstracts a COP to the interactions between a network o
466,,Hybrid Deep Learning Models for Tennis Action Recognition: Enhancing Professional Training Through CNN‐BiLSTM Integration,Zhaokun Chen; Qin Xie; Wei Jiang,2025,Concurrency and Computation,,,,,0,0.000,0.000,10.1002/cpe.70029,https://www.semanticscholar.org/paper/d2e059e3c569969d8d7a49facdc2d284b8b94881,,semantic_scholar,,"Classifying tennis movements from video data presents significant challenges, including overfitting, limited datasets, low accuracy, and difficulty in capturing dynamic, real‐world conditions such as variable lighting, camera angles, and complex player movements. Existing approaches lack robustness "
467,,Participatory Heritage Documentation: Low-cost Photogrammetry of Decayed Historic Buildings in the Medina of Tunis,Mara Cruz; Alejandra Albuerne,2025,"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",,,,,0,0.000,0.000,10.5194/isprs-archives-xlviii-m-9-2025-375-2025,https://www.semanticscholar.org/paper/46ad4a58f799ac41d60f67159a0a7a0288f0d3ad,,semantic_scholar,,"Abstract. This paper presents a low-cost, community-led documentation approach for endangered historic buildings in the Medina of Tunis, a UNESCO World Heritage Site facing significant conservation challenges. Focusing on Fondok El Henna—an abandoned caravanserai in a state of advanced decay—the stu"
468,,Abstract LB169: Machine learning-based approach for glioblastoma drug repurposing on real-world patient data,Ko-Hong Lin; Yejin Kim; Dung-Fang Lee; Xiaoqian Jiang,2023,Cancer Research,,,,,1,0.000,0.000,10.1158/1538-7445.am2023-lb169,https://www.semanticscholar.org/paper/c9069e3d0fda203bfa132a60382dfd098d4dc247,,semantic_scholar,,"
 Glioblastoma (GBM) is the most aggressive and deadly type of brain cancer. The poor survival rate of GBM is often attributed to the low therapeutic efficiency of current front-line therapy, treatment resistance, and high recurrence rate. Sizeable clinical data of cancer patients preserve a great p"
469,,OMGSR: You Only Need One Mid-timestep Guidance for Real-World Image Super-Resolution,Zhiqiang Wu; Zhaomang Sun; Tong Zhou; Bingtao Fu; Ji Cong,2025,arXiv.org,,,,,1,0.000,0.000,10.48550/arXiv.2508.08227,https://www.semanticscholar.org/paper/cc19f5eeaafe03a94a99e501ea47d27854700422,,semantic_scholar,,Denoising Diffusion Probabilistic Models (DDPMs) show promising potential in one-step Real-World Image Super-Resolution (Real-ISR). Current one-step Real-ISR methods typically inject the low-quality (LQ) image latent representation at the start or end timestep of the DDPM scheduler. Recent studies h
470,,Abstract WMP81: A ChatGLM-based stroke diagnosis and prediction tool,Xiaowei Song; Jiayi Wang; Weizhi Ma; Jian Wu; Yueming Wang,2025,Stroke,,,,,0,0.000,0.000,10.1161/str.56.suppl_1.wmp81,https://www.semanticscholar.org/paper/f20cd38bd67fd6becc18ba5f068cf123e3d755ce,,semantic_scholar,,"
 Background and purpose:
 Stroke as a world-wide prevalent disease, has brought a huge burden to health care and the national economy, accurate and fast stroke diagnosis can significantly increase reperfusion rate, mitigate disability, and reduce deaths. However, there exists a great discrepancy in"
471,,Impact of Interobserver Variability in Manual Segmentation of Non-Small Cell Lung Cancer (NSCLC) Applying Low-Rank Radiomic Representation on Computed Tomography,M. Hershman; B. Yousefi; Lacey M Serletti; M. Galperin-Aizenberg; L. Roshkovan,2021,Cancers,,,,,16,0.000,0.000,10.3390/cancers13235985,https://www.semanticscholar.org/paper/b5ba26a1c1ccf033b99706e37dc4ac6216e20a22,https://www.mdpi.com/2072-6694/13/23/5985/pdf?version=1638244067,semantic_scholar,,"Simple Summary Discovery of predictive and prognostic radiomic features in cancer is currently of great interest to the radiologic and oncologic community. Tumor phenotypic and prognostic information can be obtained by extracting features on tumor segmentations, and it is typically imaging analysts,"
472,,Directed Hypergraph Representation Learning for Link Prediction,Zitong Ma; Wenbo Zhao; Zhe Yang,2024,International Conference on Artificial Intelligence and Statistics,,,,,8,0.000,0.000,,https://www.semanticscholar.org/paper/4963e59ff7dd5ea4565dc248d4dc36378acf7f4b,,semantic_scholar,,
473,,Pixels-to-Graph: Real-time Integration of Building Information Models and Scene Graphs for Semantic-Geometric Human-Robot Understanding,Antonello Longo; Chanyoung Chung; M. Palieri; Sung-Kyun Kim; A. Agha-mohammadi,2025,2025 IEEE 21st International Conference on Automation Science and Engineering (CASE),,,,,3,0.000,0.000,10.1109/CASE58245.2025.11163791,https://www.semanticscholar.org/paper/66c926f4bd2e4ea492463b8e3bff4e02b30c661a,,semantic_scholar,,"Autonomous robots are increasingly playing key roles as support platforms for human operators in high-risk, dangerous applications. To accomplish challenging tasks, an efficient human-robot cooperation and understanding is required. While typically robotic planning leverages 3D geometric information"
474,,Abstract 5380: Systematic evaluation and comparison of drug response prediction models: a case study of prediction generalization across cell lines datasets,A. Partin; T. Brettin; Yitan Zhu; Jamie C. Overbeek; Oleksandr Narykov,2023,Cancer Research,,,,,1,0.000,0.000,10.1158/1538-7445.am2023-5380,https://www.semanticscholar.org/paper/aa55bba0c8c0c192ddf7f7a748e9ae2b01a437f5,,semantic_scholar,,"
 Predictive modeling holds great promise for improving personalized cancer treatment and efficiency of drug development. In recent years, deep learning (DL) has been extensively explored for drug response prediction (DRP), outperforming classical machine learning in prediction generalization to new"
475,,EARP: Integration with Entity Attribute and Relation Path for Event Knowledge Graph Representation Learning,Ze Xu; Hao Zhou; T. He; Huazhen Wang,2023,IEEE International Joint Conference on Neural Network,,,,,0,0.000,0.000,10.1109/IJCNN54540.2023.10191442,https://www.semanticscholar.org/paper/fbd81ce44da784c96309bb3a8a2e9fd779168c13,,semantic_scholar,,"Event knowledge graph (EKG) as a special case of knowledge graph (KG) can realize the goal of event prediction, and has been proved useful in medical diagnosis and intelligent recommendation. To successfully build an EKG, knowledge representation learning is often required to compute the semantic li"
476,,Language-Agnostic Representation Learning of Source Code from Structure and Context,Daniel Zugner; Tobias Kirschstein; Michele Catasta; J. Leskovec; Stephan Gunnemann,2021,International Conference on Learning Representations,,,,,130,0.000,0.000,,https://www.semanticscholar.org/paper/05e396e79a2f88f0b8f8d99f5ab36ab3efa95c14,,semantic_scholar,,"Source code (Context) and its parsed abstract syntax tree (AST; Structure) are two complementary representations of the same computer program. Traditionally, designers of machine learning models have relied predominantly either on Structure or Context. We propose a new model, which jointly learns on"
477,,"Abstract PD12-02: PD12-02 Obesity is associated with poor breast cancer prognosis, particularly among women with low socioeconomic position",S. Harborg; Maria Feldt; D. Cronin-Fenton; S. Dalton; A. Rosendahl,2023,Cancer Research,,,,,0,0.000,0.000,10.1158/1538-7445.sabcs22-pd12-02,https://www.semanticscholar.org/paper/73301e506d93aca224ed05a1a1af5ea632b2c40c,,semantic_scholar,,"
 Purpose: To examine the association between obesity and breast cancer outcomes and to describe socioeconomic position (SEP) in patients enrolled in the Malmö Diet and Cancer Study (MDCS) according to anthropometric measures. Patients and methods: The MDCS is a prospective cohort study that enrolle"
478,,LDWLE: self-supervised driven low-light object detection framework,Xiaoyang Shen; Haibin Li; Yaqian Li; Wenming Zhang,2024,Complex & Intelligent Systems,,,,,7,0.000,0.000,10.1007/s40747-024-01681-z,https://www.semanticscholar.org/paper/721c7db7f5cdaa9894da49d0ef3ad824b2cdeef9,https://doi.org/10.1007/s40747-024-01681-z,semantic_scholar,,"Low-light object detection involves identifying and locating objects in images captured under poor lighting conditions. It plays a significant role in surveillance and security, night pedestrian recognition, and autonomous driving, showcasing broad application prospects. Most existing object detecti"
479,,Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment,Shibbir Ahmed; Hongyang Gao; Hridesh Rajan,2024,International Conference on Software Engineering,,,,,3,0.000,0.000,10.1145/3597503.3623333,https://www.semanticscholar.org/paper/0e4468ec45f98ed60b864dae272e018e30994a17,https://dl.acm.org/doi/pdf/10.1145/3597503.3623333,semantic_scholar,,Deep learning models are trained with certain assumptions about the data during the development stage and then used for prediction in the deployment stage. It is important to reason about the trustworthiness of the model's predictions with unseen data during deployment. Existing methods for specifyi
480,,Understanding the model representation of clouds based on visible and infrared satellite observations,S. Geiss; L. Scheck; A. de Lózar; M. Weissmann,2021,Atmospheric Chemistry and Physics,,,,,10,0.000,0.000,10.5194/ACP-21-12273-2021,https://www.semanticscholar.org/paper/781f8f492167cbcf27c6b0d797283e99f667c18d,https://acp.copernicus.org/articles/21/12273/2021/acp-21-12273-2021.pdf,semantic_scholar,,"Abstract. There is a rising interest in improving the representation of clouds in numerical weather prediction models. This will directly lead to improved radiation forecasts and, thus, to better predictions of the increasingly important production of photovoltaic power. Moreover, a more accurate re"
481,,Integrating Content-Semantics-World Knowledge to Detect Stress from Videos,Yang Ding; Yi Dai; Xin Wang; Ling Feng; Lei Cao,2024,ACM Multimedia,,,,,2,0.000,0.000,10.1145/3664647.3680584,https://www.semanticscholar.org/paper/acd21627deea7746e3d76a40c839694faa585179,,semantic_scholar,,"Stress has rapidly emerged as a significant public health concern in the contemporary society, necessitating prompt identification and effective intervention strategies. Video-based stress detection offers a non-invasive, low-cost, and mass-reaching approach for identifying stress. In this paper, we"
482,,Characterising a rock fracture rough surface using spatial continuity and kriging: a new approach to meshing coupled thermo–hydraulic–mechanical–chemical (THMC) models,G. B. Cunha; Christopher Ian McDermott,2023,Safety of Nuclear Waste Disposal,,,,,0,0.000,0.000,10.5194/sand-2-107-2023,https://www.semanticscholar.org/paper/2aea81c14e96d1c7fc2b40c84d24de7950fa72de,https://sand.copernicus.org/articles/2/107/2023/sand-2-107-2023.pdf,semantic_scholar,,"Abstract. Fluid flow through low permeability rocks is mainly accomplished through fractures. In order to model fluid flow, coupled thermo–hydraulic–mechanical–chemical (THMC) numerical models are used, which rely on fracture surface representations to construct a distribution model of the empty spa"
483,,From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs,Ahmad Naser Eddin; Jacopo Bono; David Oliveira Aparício; Hugo Ferreira; João Tiago Ascensão,2023,International Conference on AI in Finance,,,,,2,0.000,0.000,10.1145/3604237.3626842,https://www.semanticscholar.org/paper/1c34c169b8765bf4854708011b3b5854cfe4cb0c,https://arxiv.org/pdf/2307.08433,semantic_scholar,,"Many real-world datasets have an underlying dynamic graph structure, where entities and their interactions evolve over time. Machine learning models should consider these dynamics in order to harness their full potential in downstream tasks. Previous approaches for graph representation learning have"
484,,Biomechanically-Inspired Bipedal Robot Locomotion via Hybrid Gait Representation and Model-Guided Reinforcement Learning,Lijie Xie; Haoming Rong; Zujian Chen; Zi-Ye Zhou; Shaolin Mo,2025,IEEE/RJS International Conference on Intelligent RObots and Systems,,,,,0,0.000,0.000,10.1109/IROS60139.2025.11247253,https://www.semanticscholar.org/paper/e5bc26ed598441c70fe81af0edeaa71c80006d20,,semantic_scholar,,"Achieving stable and natural locomotion in bipedal robots, comparable to that of humans and animals, remains a long-standing challenge in robotics. In this work, we propose a bio-inspired low-level control framework that streamlines the generation of naturalistic gait patterns while ensuring adaptab"
485,,Deep Fuzzy Framework for Emotion Recognition using EEG Signals and Emotion Representation in Type-2 Fuzzy VAD Space,Mohammad Asif; Noman Ali; Sudhakar Mishra; Anushka Dandawate; U. Tiwary,2024,arXiv.org,,,,,3,0.000,0.000,10.48550/arXiv.2401.07892,https://www.semanticscholar.org/paper/6c6c7748c18f90bb337ce6a6766d13d613d6b317,,semantic_scholar,,"Recently, the representation of emotions in the Valence, Arousal and Dominance (VAD) space has drawn enough attention. However, the complex nature of emotions and the subjective biases in self-reported values of VAD make the emotion model too specific to a particular experiment. This study aims to d"
486,,Chaotic oceanic excitation of low-frequency polar motion variability,L. Börger; M. Schindelegger; Mengnan Zhao; Rui M. Ponte; Anno Löcher,2025,Earth System Dynamics,,,,,1,0.000,0.000,10.5194/esd-16-75-2025,https://www.semanticscholar.org/paper/b7bffb47127da2a558be144e80400cff80d0ef0d,https://doi.org/10.5194/esd-16-75-2025,semantic_scholar,,"Abstract. Studies of Earth rotation variations generally assume that changes in non-tidal oceanic angular momentum (OAM) manifest the ocean's direct response to atmospheric forces. However, fluctuations in OAM may also arise from chaotic intrinsic ocean processes that originate in local nonlinear (e"
487,,"Carbonyl Sulfide: Comparing a Mechanistic Representation of 
the Vegetation Uptake in a Land Surface Model and the Leaf
Relative Uptake Approach",F. Maignan; C. Abadie; M. Remaud; Linda M. J. Kooiijmans; Kukka‐Maaria Kohonen,2020,,,,,,34,0.000,0.000,10.5194/bg-2020-381,https://www.semanticscholar.org/paper/4eb3bb5a0c3f464573b0e15d3dd6c86a4493fab5,https://bg.copernicus.org/articles/18/2917/2021/bg-18-2917-2021.pdf,semantic_scholar,,"Abstract. Land surface modelers need measurable proxies to constrain the quantity of carbon dioxide (CO2) assimilated by continental plants through photosynthesis, known as Gross Primary Production (GPP). Carbonyl sulfide (COS), which is taken up by leaves through their stomates and then hydrolysed "
488,,Simulation-Based Education of Health Workers in Low- and Middle-Income Countries: A Systematic Review,Samuel James Alexander Robinson; Angus M A Ritchie; Maurizio Pacilli; Debra Nestel; Elizabeth McLeod,2024,Global Health: Science and Practice Journal,,,,,3,0.000,0.000,10.9745/GHSP-D-24-00187,https://www.semanticscholar.org/paper/9743a0745c95b77899f87c19e9962c1d6fb852be,https://www.ghspjournal.org/content/ghsp/early/2024/11/07/GHSP-D-24-00187.full.pdf,semantic_scholar,,Simulation-based education has been widely applied in low- and middle-income countries and has been shown to improve outcomes in a variety of contexts. Key Findings Simulation-based education (SBE) has been successfully applied to improve outcomes in a variety of contexts across low- and middle-inco
489,,Real-World Robot Control by Deep Active Inference With a Temporally Hierarchical World Model,Kentaro Fujii; Shingo Murata,2025,IEEE Robotics and Automation Letters,,,,,0,0.000,0.000,10.1109/LRA.2025.3636032,https://www.semanticscholar.org/paper/173ba8ae4582b6f9f6919aa3f813579a5349f1f9,,semantic_scholar,,"Robots in uncertain realworld environments must perform both goaldirected and exploratory actions. However, most deep learning-based control methods neglect exploration and struggle under uncertainty. To address this, we adopt deep active inference, a framework that accounts for human goal-directed "
490,,Classification of Interacting Topological Crystalline Superconductors in Three Dimensions and Beyond,Shang-Qiang Ning; Xing-Yu Ren; Qing-Rui Wang; Yang Qi; Zheng-Cheng Gu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25069v1,https://arxiv.org/pdf/2512.25069v1,arxiv,,"Although classification for free-fermion topological superconductors (TSC) is established, systematically understanding the classification of 3D interacting TSCs remains difficult, especially those protected by crystalline symmetries like the 230 space groups. We build up a general framework for sys"
491,,No-cost Bell Nonlocality Certification from Quantum Tomography and Its Applications in Quantum Magic Witnessing,Pawel Cieslinski; Lukas Knips; Harald Weinfurter; Wieslaw Laskowski,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25068v1,https://arxiv.org/pdf/2512.25068v1,arxiv,,"Tomographic measurements are the standard tool for characterizing quantum states, yet they are usually regarded only as means for state reconstruction or fidelity measurement. Here, we show that the same Pauli-basis measurements (X, Y, Z) can be directly employed for the certification of nonlocality"
492,,Emergence of 3D Superconformal Ising Criticality on the Fuzzy Sphere,Yin Tang; Cristian Voinea; Liangdong Hu; Zlatko Papić; W. Zhu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25054v1,https://arxiv.org/pdf/2512.25054v1,arxiv,,"Supersymmetric conformal field theories (SCFTs) form a unique subset of quantum field theories which provide powerful insights into strongly coupled critical phenomena. Here, we present a microscopic and non-perturbative realization of the three-dimensional $\mathcal{N}=1$ superconformal Ising criti"
493,,Arithmetic with spatiotemporal optical vortex of integer and fractional topological charges,Hsiao-Chih Huang; Chen-Ting Liao; Hui Min Leung,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25049v1,https://arxiv.org/pdf/2512.25049v1,arxiv,,"Spatiotemporal optical vortices carry transverse orbital angular momentum (t-OAM), which give rise to spatiotemporal topological charge (ST-TC). To unleash the full potential of t-OAM in expanding the capacity of communication and computing, we demonstrate the first optical information-processing pi"
494,,All optical Lithography for Spatiotemporal Patterning of Azopolymer Microreliefs,I Komang Januariyasa; Francesco Reda; Nikolai Liubimtsev; Marina Saphiannikova; Fabio Borbone,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25048v1,https://arxiv.org/pdf/2512.25048v1,arxiv,,"Microstructured surfaces are central to photonics, biointerfaces, and functional coatings, yet they are typically fabricated through multi-step lithographic workflows requiring masks or molds and post-processing. Azopolymers provide an alternative route by converting structured optical fields into s"
495,,Amplitude constraints on dark energy,Scott Melville,2025,arXiv,,,,,0,0.000,0.000,10.58027/3q8k-ew90,http://arxiv.org/abs/2512.25047v1,https://arxiv.org/pdf/2512.25047v1,arxiv,,"This talk gives a short introduction to the ``UV/EFT correspondence"", which uses scattering amplitudes to relate the Effective Field Theory (EFT) coefficients probed by low-energy measurements to properties of the underlying high-energy (UV) completion. This includes recent ``positivity bounds"" on E"
496,,Approximation Algorithms for Fair Repetitive Scheduling,Danny Hermelin; Danny Segev; Dvir Shabtay,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25020v1,https://arxiv.org/pdf/2512.25020v1,arxiv,,"We consider a recently introduced fair repetitive scheduling problem involving a set of clients, each asking for their associated job to be daily scheduled on a single machine across a finite planning horizon. The goal is to determine a job processing permutation for each day, aiming to minimize the"
497,,At the intersection of Numerical Analysis and Spectral Geometry,Nilima Nigam,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25012v1,https://arxiv.org/pdf/2512.25012v1,arxiv,,"How do the geometric properties of a domain impact the spectrum of an operator defined on it? How do we compute accurate and reliable approximations of these spectra? The former question is studied in spectral geometry, and the latter is a central concern in numerical analysis. In this short exposit"
498,,Melting curve of correlated iron at Earth's core conditions from machine-learned DFT+DMFT,Rishi Rao; Li Zhu,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25061v1,https://arxiv.org/pdf/2512.25061v1,arxiv,,"Reliable constraints on iron's melting curve at Earth's inner-core boundary require accurate finite-temperature electronic correlations, yet DFT+DMFT calculations remain too costly for large-scale thermodynamic sampling. Here, we develop a machine-learning accelerator for charge self-consistent DFT+"
499,,Thin Tree Verification is coNP-Complete,Alice Moayyedi,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25043v1,https://arxiv.org/pdf/2512.25043v1,arxiv,,"An $α$-thin tree $T$ of a graph $G$ is a spanning tree such that every cut of $G$ has at most an $α$ proportion of its edges in $T$. The Thin Tree Conjecture proposes that there exists a function $f$ such that for any $α> 0$, every $f(α)$-edge-connected graph has an $α$-thin tree. Aside from its ind"
500,,Combining declarative and linear programming for application management in the cloud-edge continuum,Stefano Forti,2025,Future Generation Computer Systems,,,,,0,0.000,0.000,10.1016/j.future.2025.108224,https://openalex.org/W4416543429,https://arxiv.org/pdf/2504.12032,openalex,,
501,,EEmo-Bench: A Benchmark for Multi-modal Large Language Models on Image Evoked Emotion Assessment,Lanting Gao; Ziheng Jia; Yunhao Zeng; Wei Sun; Yiming Zhang,2025,,,,,,1,0.000,0.000,10.1145/3746027.3755777,https://openalex.org/W4415538347,https://arxiv.org/pdf/2504.16405,openalex,,"The furnishing of multi-modal large language models (MLLMs) has led to the emergence of numerous benchmark studies, particularly those evaluating their perception and understanding capabilities. Among these, understanding image-evoked emotions aims to enhance MLLMs' empathy, with significant applica"
502,,AudioSet-R: A Refined AudioSet with Multi-Stage LLM Label Reannotation,Yining Sun; Qisheng Xu; Yi Su; Qian Zhu; Yong Dou,2025,,,,,,0,0.000,0.000,10.1145/3746027.3758260,https://openalex.org/W4415539635,https://arxiv.org/pdf/2508.15429,openalex,,"AudioSet is a widely used benchmark in the audio research community and has significantly advanced various audio-related tasks. However, persistent issues with label accuracy and completeness remain critical bottlenecks that limit performance in downstream applications.To address the aforementioned "
503,,Active Learning for Neurosymbolic Program Synthesis,Celeste Barnaby; Qiaochu Chen; Ramya Ramalingam; Osbert Bastani; Işıl Dillig,2025,Proceedings of the ACM on Programming Languages,,,,,1,0.000,0.000,10.1145/3763102,https://openalex.org/W4414977305,https://doi.org/10.1145/3763102,openalex,,"The goal of active learning for program synthesis is to synthesize the desired program by asking targeted questions that minimize user interaction. While prior work has explored active learning in the purely symbolic setting, such techniques are inadequate for the increasingly popular paradigm of ne"
504,,Exploring the Theory and Practice of Concurrency in the Entity-Component-System Pattern,Patrick Redmond; Jonathan Castello; José Manuel Calderón Trilla; Lindsey Kuper,2025,Proceedings of the ACM on Programming Languages,,,,,1,0.000,0.000,10.1145/3763050,https://openalex.org/W4415007629,https://doi.org/10.1145/3763050,openalex,,"The Entity-Component-System (ECS) software design pattern, long used in game development, encourages a clean separation of identity (entities), data properties (components), and computational behaviors (systems). Programs written using the ECS pattern are naturally concurrent, and the pattern offers"
505,,Mini-Batch Robustness Verification of Deep Neural Networks,Saar Tzour-Shaday; Dana Drachsler-Cohen,2025,Proceedings of the ACM on Programming Languages,,,,,0,0.000,0.000,10.1145/3763150,https://openalex.org/W4414988741,https://doi.org/10.1145/3763150,openalex,,"Neural network image classifiers are ubiquitous in many safety-critical applications. However, they are susceptible to adversarial attacks. To understand their robustness to attacks, many local robustness verifiers have been proposed to analyze є-balls of inputs. Yet, existing verifiers introduce a "
506,,Let’s Take Esoteric Programming Languages Seriously,Jeremy Singer; Stephen Draper,2025,,,,,,0,0.000,0.000,10.1145/3759429.3762632,https://openalex.org/W4415009061,https://dl.acm.org/doi/pdf/10.1145/3759429.3762632,openalex,,"Esoteric programming languages are challenging to learn, but their unusual features and constraints may serve to improve programming ability. From languages designed to be intentionally obtuse (e.g. INTERCAL) to others targeting artistic expression (e.g. Piet) or exploring the nature of computation "
507,,A Survey on Stereotype Detection in Natural Language Processing,Alessandra Teresa Cignarella; Anastasia Giachanou; Els Lefever,2025,ACM Computing Surveys,,,,,0,0.000,0.000,10.1145/3770754,https://openalex.org/W4414863587,https://doi.org/10.1145/3770754,openalex,,"Abstract. Stereotypes influence social perceptions and can escalate into discrimination and violence. While NLP research has extensively addressed gender bias and hate speech, stereotype detection remains an emerging field with significant societal implications. This work presents a survey of existi"
508,,Demystifying Reward Design in Reinforcement Learning for Upper Extremity Interaction: Practical Guidelines for Biomechanical Simulations in HCI,Hannah Selder; Florian Fischer; Per Ola Kristensson; Arthur Fleig,2025,,,,,,0,0.000,0.000,10.1145/3746059.3747779,https://openalex.org/W4416051537,https://arxiv.org/pdf/2508.15727,openalex,,"Designing effective reward functions is critical for reinforcement learning-based biomechanical simulations, yet HCI researchers and practitioners often waste (computation) time with unintuitive trial-and-error tuning. This paper demystifies reward function design by systematically analyzing the imp"
509,,A Comparison of Deep Recurrent Neural Networks and Bayesian Neural Networks for Detecting Electric Motor Damage Through Sound Signal Analysis,Waldemar Bauer; Jerzy Baranowski,2025,Energies,,,,,0,0.000,0.000,10.3390/en18184997,https://openalex.org/W4414350374,https://www.mdpi.com/1996-1073/18/18/4997/pdf?version=1758291824,openalex,,"Fault detection in electric motors represents a critical challenge across various industries, as failures can lead to substantial operational disruptions. This study examines the application of deep neural networks (DNNs) and Bayesian neural networks (BNNs) for diagnosing motor faults through acoust"
510,,Cross-dialectal Arabic translation: comparative analysis on large language models,Ayah Beidas; Kousar Mohi; Fatme Ghaddar; Imtiaz Ahmad; Sa’ed Abed,2025,Frontiers in Artificial Intelligence,,,,,0,0.000,0.000,10.3389/frai.2025.1661789,https://openalex.org/W4414306244,https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1661789/pdf,openalex,,Introduction Exploring Arabic dialects in Natural Language Processing (NLP) is essential to understand linguistic variation and meet regional communication demands. Recent advances in Large Language Models (LLMs) have opened up new vistas for multilingual communication and text generation. Methods T
511,,Contextual Object Grouping (COG): A Specialized Framework for Dynamic Symbol Interpretation in Technical Security Diagrams,Jan Kapusta; Waldemar Bauer; Jerzy Baranowski,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.1632.v1,https://openalex.org/W4414316176,https://www.preprints.org/frontend/manuscript/2d2b3994b4fdf640f3429201e278dbc2/download_pub,openalex,,"This paper introduces Contextual Object Grouping (COG), a specific computer vision framework that enables automatic interpretation of technical security diagrams through dynamic legend learning for intelligent sensing applications. Unlike traditional object detection approaches that rely on post-pro"
512,,The Spike Processing Unit (SPU): An IIR Filter Approach to Hardware-Efficient Spiking Neurons,Hugo Puertas de Araújo,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.1538.v1,https://openalex.org/W4414316519,https://www.preprints.org/frontend/manuscript/71d8775d9605f44e736b3d3ce28e3e42/download_pub,openalex,,"This paper introduces the Spike Processing Unit (SPU), a novel digital spiking neuron model engineered for ultra-efficient hardware implementation. Departing from biologically-plausible models, the SPU prioritizes computational performance by leveraging a discrete-time Infinite Impulse Response (IIR"
513,,A Review of Socially Assistive Robotics in Supporting Children with Autism Spectrum Disorder,Muhammad Nadeem; Julien Moussa H. Barakat; Dani Daas; Albert Potams,2025,Multimodal Technologies and Interaction,,,,,0,0.000,0.000,10.3390/mti9090098,https://openalex.org/W4414328943,https://www.mdpi.com/2414-4088/9/9/98/pdf?version=1758202820,openalex,,This study aimed to investigate the use of social robots as an interactive learning approach for treating children diagnosed with autism spectrum disorder (ASD). A review was conducted using the meta-analysis technique to compile pertinent research. An analysis was performed on the results of the on
514,,An Interdisciplinary Review on Application of Graph Theory,Poonam Chawla,2025,Turkish Journal of Computer and Mathematics Education (TURCOMAT).,,,,,0,0.000,0.000,10.61841/turcomat.v9i1.15333,https://openalex.org/W4414333317,https://www.turcomat.org/index.php/turkbilmat/article/download/15333/10930,openalex,,"Graph theory is a branch of discrete mathematics that is used to model and analyze interconnected systems. This paper presents a review on application of its concepts and algorithms that support diverse applications in computer science, biology, neuroscience, social sciences, engineering and geoscie"
515,,Meta-Analysis of Artificial Intelligence’s Influence on Competitive Dynamics for Small- and Medium-Sized Financial Institutions,Macy Cudmore; David R. Mattie,2025,Analytics,,,,,0,0.000,0.000,10.3390/analytics4030024,https://openalex.org/W4414336294,https://www.mdpi.com/2813-2203/4/3/24/pdf?version=1758175607,openalex,,"Artificial intelligence adoption in financial services presents uncertain implications for competitive dynamics, particularly for smaller institutions. The literature on AI in finance is growing, but there remains a notable absence regarding the impacts on small- and medium-sized financial services "
516,,Mitigating Anomaly-Based DDoS Attack in Heterogeneous IoT Networks with a Federated Learning Model,MUTHUKUMARAN Chellaperumal; S. Radhakrishnan; Sivarajan Ganesan,2025,ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH,,,,,0,0.000,0.000,10.24818/18423264/59.3.25.11,https://openalex.org/W4414339635,https://doi.org/10.24818/18423264/59.3.25.11,openalex,,
517,,Two-Step Forward Modeling for GPR Data of Metal Pipes Based on Image Translation and Style Transfer,Zhishun Guo; Yesheng Gao; Zicheng Huang; Mengyang Shi; Xingzhao Liu,2025,Remote Sensing,,,,,0,0.000,0.000,10.3390/rs17183215,https://openalex.org/W4414282087,https://www.mdpi.com/2072-4292/17/18/3215/pdf?version=1758115071,openalex,,"Ground-penetrating radar (GPR) is an important geophysical technique in subsurface detection. However, traditional numerical simulation methods such as finite-difference time-domain (FDTD) face challenges in accurately simulating complex heterogeneous mediums in real-world scenarios due to the diffi"
518,,An Innovative Retrieval-Augmented Generation Framework for Stage-Specific Knowledge Translation in Biomimicry Design,Hsueh-Kuan Chen; Hung-Hsiang Wang,2025,Biomimetics,,,,,0,0.000,0.000,10.3390/biomimetics10090626,https://openalex.org/W4414283556,https://www.mdpi.com/2313-7673/10/9/626/pdf?version=1758108308,openalex,,"Converting biological strategies into practical design principles during the Discover–Abstract phase of the Biomimicry Design Spiral (BSD) presents a considerable obstacle, particularly for designers lacking a biological background. This research introduces a Retrieval-Augmented Generation (RAG) fra"
519,,Flood Prediction with Artificial Intelligence An Exploratory Data Analysis Approach,Anna Mané; Rashmi Ravindra Halkarni; P. N. Bhat; Amarnath Mahesh Kakatikar; Rajkumar V. Raikar,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-7063048/v1,https://openalex.org/W4414305077,https://www.researchsquare.com/article/rs-7063048/latest.pdf,openalex,,<title>Abstract</title> This paper presents the application of various ML and DL algorithms to de- termine occurrence of floods in India. In this study data driven methods are used which could help in predicting floods on a national and regional level. Using a real- world dataset containing environm
520,,Building Sequences of Ads Relying on Discourse Analysis,Boris Galitsky,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.1423.v1,https://openalex.org/W4414315874,https://www.preprints.org/frontend/manuscript/cc931dba5de25185abee213de4088103/download_pub,openalex,,"We propose a method for generating sequences of advertisements derived from product descriptions and targeting keywords. Each sequence functions as a narrative, guiding potential customers through a storytelling journey. The sequence begins by building brand awareness, then highlights key product fe"
521,,Anticipatory Semantics with Bidirectional Guidance for Image Captioning,Nathalie Laurent; Elodie Fairchild; Arthur Delvaux,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.1497.v1,https://openalex.org/W4414315887,https://www.preprints.org/frontend/manuscript/3a90020e8e0ebfd0b1934a961c7a89ba/download_pub,openalex,,"Producing captions that are not only grammatically fluent but also semantically faithful to visual content has long stood as a central problem at the junction of computer vision and natural language processing. Conventional encoder-decoder frameworks with attention modules, although powerful, typica"
522,,Development of effective methods and tools for the auditing AI algorithms by Supreme Audit Institutions,Dirk Brand; McElory Hoffmann; Johan Van der Merwe,2025,JeDEM - eJournal of eDemocracy and Open Government,,,,,0,0.000,0.000,10.29379/jedem.v17i3.1049,https://openalex.org/W4414328684,https://jedem.org/index.php/jedem/article/download/1049/619,openalex,,"This article proposes an AI Audit Framework for Supreme Audit Institutions, focusing on public sector usage. It addresses the need for transparency, fairness, accountability, and alignment with ethical and legal requirements. The authors discuss the rise of AI, particularly generative AI and large l"
523,,Impact of Information Sharing and Blockchain Technology on Supply Chain Performance,Yang Lu; Liang Yu-hua; Binbin Lan,2025,International Journal of Information Systems and Supply Chain Management,,,,,1,0.000,0.000,10.4018/ijisscm.389058,https://openalex.org/W4414240450,https://www.igi-global.com/ViewTitle.aspx?TitleId=389058&isxn=9798337311654,openalex,,"This study examines the impact of information technology, particularly blockchain, on enhancing supply chain performance amidst increasing complexity and competition. An agent-based model simulates a four-tier supply chain (consumers, retailers, distributors, suppliers) across three scenarios—no inf"
524,,Fintech Converges with Investment and Risk: A Bibliometric Review,Michael Chuang; Sunil Shrestha,2025,Journal of risk and financial management,,,,,0,0.000,0.000,10.3390/jrfm18090517,https://openalex.org/W4414240305,https://www.mdpi.com/1911-8074/18/9/517/pdf?version=1758029148,openalex,,"The rapid growth of fintech is revolutionizing the delivery, access, and management of financial services. It also presents new risks and opportunities for investment. Despite growing scholarly interest, current research often remains fragmented and continues to explore technological innovation, inv"
525,,A New Method Based on Hierarchical Belief Rule Base with Balanced Accuracy and Interpretability for Stock Price Trend Prediction,Jiaxing Li; Boyu Liu; Wenkai Zhou; Tianhao Zhang; Xiping Duan,2025,Symmetry,,,,,0,0.000,0.000,10.3390/sym17091550,https://openalex.org/W4414247080,https://www.mdpi.com/2073-8994/17/9/1550/pdf?version=1758016277,openalex,,"The prediction of stock price trends is of vital importance for maintaining the stability of the financial market, optimizing resource allocation and preventing systemic risks. To ensure the practical application value of the prediction model, it is necessary to maintain prediction accuracy while en"
526,,Machine Learning for Optimizing Urban Photovoltaics: A Review of Static and Dynamic Factors,Mahdiyeh Tabatabaei; Ernesto Antonini,2025,Sustainability,,,,,0,0.000,0.000,10.3390/su17188308,https://openalex.org/W4414298792,https://www.mdpi.com/2071-1050/17/18/8308/pdf?version=1758027754,openalex,,"Cities need photovoltaic (PV) systems to meet climate-neutral goals, yet dense urban forms and variable weather limit their output. This review synthesizes how machine learning (ML) models capture both static factors (orientation, roof, and façade geometry) and dynamic drivers (irradiance, transient"
527,,"Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property Prediction",David Graff; Nathan Morgan; Jackson Burns; Anna C. Doner; Bingxue Li,2025,,,,,,0,0.000,0.000,10.26434/chemrxiv-2025-4p1nr,https://openalex.org/W4414189271,https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/68bb5b5b23be8e43d65c5cc5/original/chemprop-v2-an-efficient-modular-machine-learning-package-for-chemical-property-prediction.pdf,openalex,,"Accurate prediction of molecular properties is essential for computational design in many areas of chemistry. Deep learning has been used in these prediction tasks for a wide variety of molecular properties, and the availability of user-friendly, open-source software implementing such architectures "
528,,Trustworthy Software States through Attestation and Secure Updates,Ahmad B. Usman,2025,Linköping studies in science and technology. Thesis,,,,,0,0.000,0.000,10.3384/9789181182347,https://openalex.org/W4414193558,https://liu.diva-portal.org/smash/get/diva2:1997850/FULLTEXT01,openalex,,"Computing systems are widespread in modern society, ranging from everyday personal devices to critical infrastructures such as embedded systems, industrial control systems, cloud servers, and IoT devices. Given this widespread integration, it is essential to check the state of these software systems"
529,,On Valence: A Self-Predictive Processing Model of Emotion Regulation,Yuyue Jiang,2025,,,,,,0,0.000,0.000,10.31234/osf.io/czuqw_v1,https://openalex.org/W4414194805,https://osf.io/czuqw_v1/download,openalex,,"Emotion regulation is a fundamental process that shapescognitive, affective, and behavioral responses to emotionalstimuli. Traditional emotion regulation models conceptualizeregulation as a sequential modulation of emotional responses.However, they do not fully explain how emotions areconstructed in"
530,,"Large Language Model Agents for Biomedicine: A Comprehensive Review of Methods, Evaluations, Challenges, and Future Directions",Xiaoran Xu; Ravi Sankar,2025,,,,,,0,0.000,0.000,10.22541/au.175795684.47167615/v1,https://openalex.org/W4414199736,https://www.authorea.com/doi/pdf/10.22541/au.175795684.47167615/v1,openalex,,"Large language model (LLM) based agents are rapidly emerging as transformative tools across biomedical research and clinical applications. By integrating reasoning, planning, memory, and tool use capabilities, these agents go beyond static language models to operate autonomously or collaboratively w"
531,,Exploring Sign Language Dataset Augmentation with Generative Artificial Intelligence Videos: A Case Study Using Adobe Firefly-Generated American Sign Language Data,Valentin Bercaru; Nirvana Popescu,2025,Information,,,,,0,0.000,0.000,10.3390/info16090799,https://openalex.org/W4414205131,https://www.mdpi.com/2078-2489/16/9/799/pdf?version=1757930835,openalex,,"Currently, high quality datasets focused on Sign Language Recognition are either private, proprietary or difficult to obtain due to costs. Therefore, we aim to mitigate this problem by augmenting a publicly available dataset with artificially generated data in order to enrich and obtain a more diver"
532,,Designing A STEM-Based Instructional Unit Using Matlab-Simulink: A Pedagogical Framework For Technical Education,Abdo Qaisi,2025,International Journal For Multidisciplinary Research,,,,,0,0.000,0.000,10.36948/ijfmr.2025.v07i05.55288,https://openalex.org/W4414292648,https://www.ijfmr.com/papers/2025/5/55288.pdf,openalex,,This paper presents a pedagogical framework for designing an integrated STEM instructional unit at the undergraduate level that leverages MATLAB-Simulink as a core teaching tool. The framework aligns with established educational theories and curriculum standards to enhance technical education throug
533,,Resilient State-Space Network: A dynamically adaptive framework for non-linear modelling of temporal dependencies,Chenyu Xue; Zhentan Quan; Zhaofang Yang; Heng Zhang,2025,Journal of Computational Design and Engineering,,,,,0,0.000,0.000,10.1093/jcde/qwaf092,https://openalex.org/W4414347317,https://academic.oup.com/jcde/advance-article-pdf/doi/10.1093/jcde/qwaf092/64272693/qwaf092.pdf,openalex,,"Abstract Time-series modelling plays a central role in machine learning applications such as speech processing, biosignal analysis, and emotion recognition. Despite recent advances, existing models still face fundamental challenges in capturing complex temporal patterns, especially in scenarios invo"
534,,Knowledge-Aware Arabic Question Generation: A Transformer-Based Framework,Reham Bin Jabr; Aqil M. Azmi,2025,Mathematics,,,,,0,0.000,0.000,10.3390/math13182975,https://openalex.org/W4414181186,https://www.mdpi.com/2227-7390/13/18/2975/pdf?version=1757846997,openalex,,"In this work, we propose a knowledge-aware approach for Arabic automatic question generation (QG) that leverages the multilingual T5 (mT5) transformer augmented with a pre-trained Arabic question-answering model to address challenges posed by Arabic’s morphological richness and limited QG resources."
535,,"Impact of Artificial Intelligence on Education and Research: Pedagogy, Learning Analytics, and Academic Transformation",Sasmita Padhy,2025,,,,,,0,0.000,0.000,10.70593/978-93-7185-525-9,https://openalex.org/W4414201528,https://www.deepscienceresearch.com/dsr/catalog/download/304/1459/2845,openalex,,"This book discusses the impact of artificial intelligence on academic practice and research. This book demonstrates how AI and its applications in teaching, learning, and discovery impact opportunities for educational and scientific innovation. The description raises the good, and the bad, moral con"
536,,Optimizing Symbolic Execution Path Exploration with a Transfer Learning-Based Strategy,Te Sun; Dongqing Zhu; Lianying He; Dalin Zhang,2025,International Journal of Computers Communications & Control,,,,,0,0.000,0.000,10.15837/ijccc.2025.5.6885,https://openalex.org/W4414116872,https://univagora.ro/jour/index.php/ijccc/article/download/6885/2394,openalex,,"aSymbolic execution is an important software analysis technique, but it faces challenges such as path explosion, which leads to a reduction in efficiency. Existing path exploration strategies, such as Random State Search, typically exhibit poor adaptability to real-world programs and lack effective "
537,,Emergent Semantics from Disjoint Modalities: Unsupervised Cross-Domain Vision-Language Grounding,Maddy Janssens; Nemo Peeters; Callum Hensley,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.0958.v1,https://openalex.org/W4414117317,https://www.preprints.org/frontend/manuscript/f1c8ec8ac15439139e608de9f4036073/download_pub,openalex,,"The rapid evolution of multimodal representation learning has yielded increasingly powerful vision-and-language (V\&amp;amp;L) systems, achieving remarkable success across diverse downstream tasks. Yet, most current solutions are fundamentally constrained by their dependence on large-scale parallel "
538,,A Hierarchy of Learning Problems: Computational Efficiency Mappings for Optimization Algorithms,Michael Rey,2025,Preprints.org,,,,,0,0.000,0.000,10.20944/preprints202509.0955.v1,https://openalex.org/W4414117341,https://www.preprints.org/frontend/manuscript/6d668750a38222f0d702e5ac003c6a62/download_pub,openalex,,"We establish a rigorous mathematical hierarchy for optimization problems that serves as both theoretical classification and practitioner decision system. Problems are exhaustively categorized into three classes: (1) Non-learnable problems where no alpha-averaged operator exists, precluding iterative"
539,,AGI-Enabled Solutions for Service Explosion in IoX: A Cyber-Physical-Social-Thinking Perspective,Qingfeng Wei; Huansheng Ning; Feifei Shi; Tao Zhu; Jianguo Ding,2025,,,,,,0,0.000,0.000,10.36227/techrxiv.175760577.70793732/v1,https://openalex.org/W4414121777,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.175760577.70793732/v1,openalex,,
540,,"The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why - A Survey from MARL to Emergent Language and LLMs",Jingdi Chen; Hanqing Yang; Z Liu; Vincent W. S. Wong,2025,,,,,,0,0.000,0.000,10.36227/techrxiv.175760290.08279849/v1,https://openalex.org/W4414123240,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.175760290.08279849/v1,openalex,,
541,,Transformers and State-Space Models: Fine-Tuning Techniques for Solving Differential Equations,Vera Ignatenko; Anton Surkov; Vladimir Zakharov; Sergei Koltcov,2025,Sci,,,,,0,0.000,0.000,10.3390/sci7030130,https://openalex.org/W4414128618,https://www.mdpi.com/2413-4155/7/3/130/pdf?version=1757636937,openalex,,"Large language models (LLMs) have recently demonstrated remarkable capabilities in natural language processing, mathematical reasoning, and code generation. However, their potential for solving differential equations—fundamental to applied mathematics, physics, and engineering—remains insufficiently"
542,,Technological Evolution and Research Trends of Intelligent Question-Answering Systems in Healthcare,Bingyin Lei; P. Yin,2025,Healthcare,,,,,0,0.000,0.000,10.3390/healthcare13182269,https://openalex.org/W4414133917,https://www.mdpi.com/2227-9032/13/18/2269/pdf?version=1757569611,openalex,,Background/Objective: This study investigates the implementation and evolution of intelligent medical question-answering (QA) systems in healthcare to enhance service efficiency and quality. Methods: Through an integrated literature review and bibliometric analysis using CiteSpace 6.3.R1(64-bit) Bas
543,,Community-based participatory research to inform the design of electronic problem-solving training for individuals with traumatic brain injury (Preprint),Matthew Schmidt; Yueqi Weng; Shannon B. Juengst; Alexandra Holland,2025,,,,,,0,0.000,0.000,10.2196/preprints.83995,https://openalex.org/W4414149148,https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-83995-submitted.pdf,openalex,,"<sec> <title>BACKGROUND</title> Traditional rehabilitation research often excludes the voices of individuals with lived experience of traumatic brain injury (TBI), resulting in interventions that lack relevance, accessibility, and effectiveness. Community-Based Participatory Research (CBPR) offers a"
544,,A Multi-View Fusion Data-Augmented Method for Predicting BODIPY Dye Spectra,Xinwen Yang; Xuan Li; Qin Zhao,2025,Mathematics,,,,,0,0.000,0.000,10.3390/math13182947,https://openalex.org/W4414154447,https://www.mdpi.com/2227-7390/13/18/2947/pdf?version=1757655779,openalex,,"Fluorescent molecules, particularly BODIPY dyes, have found wide applications in fields such as bioimaging and optoelectronics due to their excellent photostability and tunable spectral properties. In recent years, artificial intelligence methods have enabled more efficient screening of molecules, a"
545,,STRIDE: Subset-Free Functional Decomposition for XAI in Tabular Settings,C KO,2025,arXiv (Cornell University),,,,,0,0.000,0.000,10.48550/arxiv.2509.09070,https://openalex.org/W4415090271,https://arxiv.org/pdf/2509.09070,openalex,,"Most explainable AI (XAI) frameworks are limited in their expressiveness, summarizing complex feature effects as single scalar values ϕ_i. This approach answers ""what"" features are important but fails to reveal ""how"" they interact. Furthermore, methods that attempt to capture interactions, like thos"
546,,Convergence of the generalization error for deep gradient flow methods for PDEs,Chenguang Liu; Antonis Papapantoleon; Jasper Rou,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25017v1,https://arxiv.org/pdf/2512.25017v1,arxiv,,The aim of this article is to provide a firm mathematical foundation for the application of deep gradient flow methods (DGFMs) for the solution of (high-dimensional) partial differential equations (PDEs). We decompose the generalization error of DGFMs into an approximation and a training error. We f
547,,The splitting field and generators of the elliptic surface $Y^2=X^3 +t^{360} +1$,Sajad Salami,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25009v1,https://arxiv.org/pdf/2512.25009v1,arxiv,,"The splitting field of an elliptic surface $\mathcal{E}/\mathbb{Q}(t)$ is the smallest finite extension $\mathcal{K} \subset \mathbb{C}$ such that all $\mathbb{C}(t)$-rational points are defined over $\mathcal{K}(t)$. In this paper, we provide a symbolic algorithmic approach to determine the splitti"
548,,Fast Poisson brackets and constraint algebras in canonical gravity,Will Barker,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25007v1,https://arxiv.org/pdf/2512.25007v1,arxiv,,"In the study of alternative or extended theories of gravity, Dirac's Hamiltonian constraint algorithm is invaluable for enumerating the propagating modes and gauge symmetries. For gravity, this canonical approach is frequently applied as a means for finding pathologies such as strongly coupled modes"
549,,Strategies for Overcoming Gradient Troughs in the ADAPT-VQE Algorithm,Jonas Stadelmann; Julian Übelher; Mafalda Ramôa; Bharath Sambasivam; Edwin Barnes,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.25004v1,https://arxiv.org/pdf/2512.25004v1,arxiv,,"The adaptive derivative-assembled problem-tailored variational quantum eigensolver (ADAPT-VQE) provides a promising approach for simulating highly correlated quantum systems on quantum devices, as it strikes a balance between hardware efficiency, trainability, and accuracy. Although ADAPT-VQE avoids"
550,,Manifold classification from the descriptive viewpoint,Jeffrey Bergfalk; Iian B. Smythe,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24996v1,https://arxiv.org/pdf/2512.24996v1,arxiv,,"We consider classification problems for manifolds and discrete subgroups of Lie groups from a descriptive set-theoretic point of view. This work is largely foundational in conception and character, recording both a framework for general study and Borel complexity computations for some of the most fu"
551,,Strong Gravitational Lensing by a Black Hole with a Global Monopole in Kalb-Ramond Bumblebee Gravity,Bijendra Kumar Vishvakarma; Shubham Kala,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24995v1,https://arxiv.org/pdf/2512.24995v1,arxiv,,"We investigate the strong gravitational lensing and shadow properties of the black hole in the context of bumblebee gravity, characterized by a global monopole charge $κη^2$ and a Lorentz symmetry breaking parameter $γ$. We compute the deflection angles of light passing near the black hole in strong"
552,,Mathieu Control of the Effective Coupling in Superconducting Qubits,Yi-Han Yu; Xin-Yi Li; Kai Xu; Heng Fan,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24992v1,https://arxiv.org/pdf/2512.24992v1,arxiv,,"A common challenge in superconducting quantum circuits is the trade-off between strong coupling and computational subspace integrity. We present Mathieu control, which uses a non-resonant two-photon drive to create a selective nonlinear frequency shift. This shift modifies interactions while preserv"
553,,The Supersymmetry of Cuts in Pure Gauge Theory and Gravity,Jacob L. Bourjaily,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24984v1,https://arxiv.org/pdf/2512.24984v1,arxiv,,"At tree-level, scattering amplitudes involving only gluons or gravitons are unaffected by supersymmetry, allowing them to be efficiently encoded by and extracted from those of maximally supersymmetric (N=4,8) theories. This fails beyond tree-level, of course, but much less than would be expected. We"
554,,Optical Spiking Neural Networks via Rogue-Wave Statistics,Bahadır Utku Kesgin; Gülsüm Yaren Durdu; Uğur Teğin,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24983v1,https://arxiv.org/pdf/2512.24983v1,arxiv,,"Optical computing could reduce the energy cost of artificial intelligence by leveraging the parallelism and propagation speed of light. However, implementing nonlinear activation, essential for machine learning, remains challenging in low-power optical systems dominated by linear wave physics. Here,"
555,,"Semiclassics, branes, and extremality",Adolfo Holguin,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24979v1,https://arxiv.org/pdf/2512.24979v1,arxiv,,"We revisit the problem of computing extremal and non-extremal three point functions of semiclassical probes with single trace operators and point out certain inconsistencies in previous approaches in the literature. We clarify the roles of wavefunctions and averaging over moduli, concluding that hol"
556,,SymSeqBench: a unified framework for the generation and analysis of rule-based symbolic sequences and datasets,Barna Zajzon; Younes Bouhadjar; Maxime Fabre; Felix Schmidt; Noah Ostendorf,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24977v1,https://arxiv.org/pdf/2512.24977v1,arxiv,,"Sequential structure is a key feature of multiple domains of natural cognition and behavior, such as language, movement and decision-making. Likewise, it is also a central property of tasks to which we would like to apply artificial intelligence. It is therefore of great importance to develop framew"
557,,Random Batch Sum-of-Gaussians Method for Molecular Dynamics of Born-Mayer-Huggins Systems,Chen Chen; Jiuyang Liang; Zhenli Xu; Qianru Zhang,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24970v1,https://arxiv.org/pdf/2512.24970v1,arxiv,,"The Born-Mayer-Huggins (BMH) potential, which combines Coulomb interactions with dispersion and short-range exponential repulsion, is widely used for ionic materials such as molten salts. However, large-scale molecular dynamics simulations of BMH systems are often limited by computation, communicati"
558,,Numerical study of solitary waves in Dirac--Klein--Gordon system,Andrew Comech; Julien Ricaud; Marco Roque,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24954v1,https://arxiv.org/pdf/2512.24954v1,arxiv,,"We use numerics to construct solitary waves in Dirac--Klein--Gordon (in one and three spatial dimensions) and study the dependence of energy and charge on $ω$. For the construction, we use the iterative procedure, starting from solitary waves of nonlinear Dirac equation, computing the corresponding "
559,,Enhancing computational efficiency in digital twins: a survey of techniques and challenges for fast inference,M. Dantas; Miguel Lpc Silva; Assis T. de Oliveira Filho; Diego de Freitas Bezerra; Eduardo Freitas,2025,Applied intelligence (Boston),,,,,0,0.000,0.000,10.1007/s10489-025-06916-1,https://www.semanticscholar.org/paper/4108ab89c6c81b8930344e919ce10db670f8a4c5,,semantic_scholar,,
560,,Design of restricted normalizing flow towards arbitrary stochastic policy with computational efficiency,Taisuke Kobayashi; Takumi Aotani,2023,Adv. Robotics,,,,,5,0.000,0.000,10.1080/01691864.2023.2208634,https://www.semanticscholar.org/paper/f3e2d9a178a353f3596b45e7360a71648ce1bbf8,,semantic_scholar,,"This paper proposes a new design method for a stochastic control policy using a normalizing flow (NF). In reinforcement learning (RL), the policy is usually modeled as a distribution model with trainable parameters. When this parameterization has less expressiveness, it would fail to acquiring the o"
561,,An Efficient Implicit Neural Representation Image Codec Based on Mixed Autoregressive Model for Low-Complexity Decoding,Xiang Liu; Jiahong Chen; Bin Chen; Zimo Liu; Baoyi An,2024,IEEE transactions on multimedia,,,,,1,0.000,0.000,10.1109/TMM.2025.3604982,https://www.semanticscholar.org/paper/95965f9d0bd5ac42e86484dd6179b526d2644489,,semantic_scholar,,"Displaying high-quality images on edge devices, such as augmented reality devices, is essential for enhancing the user experience. However, these devices often face power consumption and computing resource limitations, making it challenging to apply many deep learning-based image compression algorit"
562,,iGRLDTI: an improved graph representation learning method for predicting drug–target interactions over heterogeneous biological information network,Bowei Zhao; Xiao-Rui Su; Pengwei Hu; Yu-An Huang; Zhuhong You,2023,Bioinform.,,,,,78,0.000,0.000,10.1093/bioinformatics/btad451,https://www.semanticscholar.org/paper/eaacdc98e913f092815365308fd8026bf2e86f9c,https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btad451/50997069/btad451.pdf,semantic_scholar,,"Abstract Motivation The task of predicting drug–target interactions (DTIs) plays a significant role in facilitating the development of novel drug discovery. Compared with laboratory-based approaches, computational methods proposed for DTI prediction are preferred due to their high-efficiency and low"
563,,Comparison of a Full-Scale and a 1:10 Scale Low-Speed Two-Stroke Marine Engine Using Computational Fluid Dynamics,Flavio Chuahy; Charles E. A. Finney; Brian C. Kaul; Michael Kass,2024,ASME 2024 ICE Forward Conference,,,,,1,0.000,0.000,10.1115/icef2024-142853,https://www.semanticscholar.org/paper/cc0fdeb79e8624fc55841ef93dde6266733e3aad,,semantic_scholar,,"
 International marine shipping is a growing component of international trade; a vast majority of all the world’s goods are being transported on large ocean-going vessels. The International Maritime Organization (IMO) introduced the Energy Efficiency Design Index (EEDI) in 2013, a regulatory framewo"
564,,"Representation, Alignment, and Generation: A Comprehensive Survey of Foundation Models for Non-Invasive Brain Decoding",Yifan Wang; Shaonan Wang; Yunhao Zhang; Changde Du; Cunhang Fan,2025,bioRxiv,,,,,0,0.000,0.000,10.64898/2025.11.30.691403,https://www.semanticscholar.org/paper/4234b1e23468d2cdc7e542e98a573507f0c508d5,,semantic_scholar,,
565,,Artificial Intelligence Energy Efficiency in Low Power Applications,Dr. V. Sudha; R. Prameela Devi Sr. Assistant Professor; K.Kavitha; A. Prakash; G.Ramachandran,2023,2023 4th International Conference for Emerging Technology (INCET),,,,,2,0.000,0.000,10.1109/INCET57972.2023.10170102,https://www.semanticscholar.org/paper/a8c3a56b85fc0bd1829a0c52a1fd4e596eb52c0a,,semantic_scholar,,"In the direction of independent on-device AI .By deploying AI to edge devices, on-device AI may power a variety of functions in our daily lives, such as search and rescue with unmanned aerial vehicles, health care in robots, and augmented reality (AR)/mixed reality (XR) glasses (UAVs).However, it ca"
566,,Efficient Image Classification via Structured Low-Rank Matrix Factorization Regression,Hengmin Zhang; Jian Yang; Jianjun Qian; Guangwei Gao; Xiangyuan Lan,2024,IEEE Transactions on Information Forensics and Security,,,,,11,0.000,0.000,10.1109/TIFS.2023.3337717,https://www.semanticscholar.org/paper/d8d1e532b38bdb88603962fe65211b268ab6e92a,,semantic_scholar,,"In real-world applications involving sparse coding and low-rank matrix recovery problems, linear regression methods usually struggle to effectively capture the structured correlations present in data matrices. This limitation arises from representation approaches that treat images as vectors and han"
567,,GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds,Fei Li; Yang Lu; Qiang Ma; Shuxin Yin; Rui Zhao,2025,Frontiers in Plant Science,,,,,1,0.000,0.000,10.3389/fpls.2025.1620339,https://www.semanticscholar.org/paper/51e2005a138292598ce640f473b92ee6a1d96800,,semantic_scholar,,Deep learning models for rice pest detection often face performance degradation in real-world field environments due to complex backgrounds and limited computational resources. Existing approaches suffer from two critical limitations: (1) inadequate feature representation under occlusion and scale v
568,,Topological and Node Noise Filtering on 3D Meshes Using Graph Neural Networks (Student Abstract),Vladimir Mashurov; Natalia Semenova,2024,AAAI Conference on Artificial Intelligence,,,,,1,0.000,0.000,10.1609/aaai.v38i21.30482,https://www.semanticscholar.org/paper/4ba14f18fc5d17b99f7e57a374edeb65ba21c06f,https://ojs.aaai.org/index.php/AAAI/article/download/30482/32600,semantic_scholar,,"Topological and node noise filtration are typically considered separately. Graph Neural Networks (GNN) are commonly used for node noise filtration, as they offer high efficiency and low exploitation costs. This paper explores the solution of joint node and topological noise filtration through the us"
569,,Personalized User Models in a Real-world Edge Computing Environment: A Peer-to-peer Federated Learning Framework,Xiangchi Song; Zhaoyan Wang; Kyeong-Deok Baek; In-Young Ko,2025,Journal of Web Engineering,,,,,0,0.000,0.000,10.13052/jwe1540-9589.2381,https://www.semanticscholar.org/paper/416e47c38289458c613c9b0d170b588a73657516,,semantic_scholar,,"As the number of IoT devices and the volume of data increase, distributed computing systems have become the primary deployment solution for large-scale Internet of Things (IoT) environments. Federated learning (FL) is a collaborative machine learning framework that allows for model training using da"
570,,Fast and Accurate Power Load Data Completion via Regularization-optimized Low-Rank Factorization,Yan Xia; Hao Feng; Hongwei Sun; Junjie Wang; Qicong Hu,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2505.19133,https://www.semanticscholar.org/paper/a68d69213f422fdef08e7e5aa27b9bc421a34060,,semantic_scholar,,"Low-rank representation learning has emerged as a powerful tool for recovering missing values in power load data due to its ability to exploit the inherent low-dimensional structures of spatiotemporal measurements. Among various techniques, low-rank factorization models are favoured for their effici"
571,,Regularization-optimized Low-Rank Factorization for Power Load Data Completion,Yan Xia; Hao Feng; Hongwei Sun; Junjie Wang; Qicong Hu,2025,Proceedings of the 9th International Conference on Electronic Information Technology and Computer Engineering,,,,,0,0.000,0.000,10.1145/3766671.3766749,https://www.semanticscholar.org/paper/fb7dd08baa26f8d5b1c5fa49320bf0c8bd7e840d,,semantic_scholar,,"Low-rank representation learning has emerged as a powerful tool for recovering missing values in power load data due to its ability to exploit the inherent low-dimensional structures of spatiotemporal measurements. Among various techniques, low-rank factorization models are favored for their efficie"
572,,Efficient Low-Rank Representation for Hyperspectral Anomaly Detection via Pixel Segmentation,Kun Yu; Zebin Wu; Jing Sun; Yang Xu; Yi Zhang,2025,IEEE Transactions on Geoscience and Remote Sensing,,,,,3,0.000,0.000,10.1109/TGRS.2025.3555958,https://www.semanticscholar.org/paper/964baade88b8dc992689b0cb31c1e0e6e8b2e5c6,,semantic_scholar,,"Low-rank representation is a popularly used method in remote sensing and image processing systems. Existing low-rank representation-based algorithms often neglect the varying sensitivities of different pixels to the dictionary, which may lead to inaccurate detection. Also, the dense iterative comput"
573,,ZipZap: Efficient Training of Language Models for Large-Scale Fraud Detection on Blockchain,Sihao Hu; Tiansheng Huang; Ka-Ho Chow; Wenqi Wei; Yanzhao Wu,2024,The Web Conference,,,,,25,0.000,0.000,10.1145/3589334.3645352,https://www.semanticscholar.org/paper/dda7e51bda9556693d84500ee6dbdb346d6e5651,,semantic_scholar,,"Language models (LMs) have demonstrated superior performance in detecting fraudulent activities on Blockchains. Nonetheless, the sheer volume of Blockchain data results in excessive memory and computational costs when training LMs from scratch, limiting their capabilities to large-scale applications"
574,,Task Offloading in Internet of Vehicles: A DRL-Based Approach With Representation Learning for DAG Scheduling,Xiaoheng Deng; Haoyu Yang; Jingjing Zhang; Jinsong Gui; Siyu Lin,2025,IEEE Transactions on Mobile Computing,,,,,1,0.000,0.000,10.1109/TMC.2025.3531887,https://www.semanticscholar.org/paper/65045e6f929fd292c663a41304302711b9059439,,semantic_scholar,,"The rapid evolution of the Internet-of-Vehicles (IoV) has amplified the need for mobile computing resources, driving the shift toward offloading tasks to edge servers or vehicles with idle resources to optimize computational efficiency. To this end, an approach based on Deep Reinforcement Learning ("
575,,An Adaptive Low Computational Cost Alternating Direction Method of Multiplier for RELM Large-Scale Distributed Optimization,Ke Wang; Shanshan Huo; Banteng Liu; Zhangquan Wang; Tiaojuan Ren,2023,Mathematics,,,,,1,0.000,0.000,10.3390/math12010043,https://www.semanticscholar.org/paper/c83ec9a9c741fcf34fcdeec6b86129952f0142b1,https://www.mdpi.com/2227-7390/12/1/43/pdf?version=1703257573,semantic_scholar,,"In a class of large-scale distributed optimization, the calculation of RELM based on the Moore–Penrose inverse matrix is prohibitively expensive, which hinders the formulation of a computationally efficient optimization model. Attempting to improve the model’s convergence performance, this paper pro"
576,,Efficient Infrared Small Target Detection via Fixed-Rank Representation and Patch-Tensor Model,Yuhui Li; Peiwen Chen,2025,IEEE Transactions on Geoscience and Remote Sensing,,,,,0,0.000,0.000,10.1109/TGRS.2025.3624559,https://www.semanticscholar.org/paper/716e3479cf532272c34138776838afde5bd9b0a6,,semantic_scholar,,"Robust and efficient detection of infrared small targets is the key technology of the infrared search and tracking (IRST) system. Low-rank sparse decomposition (LRSD) is a powerful tool for infrared small target detection. However, the current LRSD-based methods generally have two crucial issues, th"
577,,Enhancing SLAM efficiency: a comparative analysis of B-spline surface mapping and grid-based approaches,B. R. Kanna; S. Av; C. S. Hemalatha; Manoj Kumar Rajagopal,2024,Applied intelligence (Boston),,,,,2,0.000,0.000,10.1007/s10489-024-05776-5,https://www.semanticscholar.org/paper/76eb89b63d9b50288850522a6a9997b887a8ea87,,semantic_scholar,,
578,,Lightweight Object Detection via Joint Region-Context Feature Representation,Chenxu Li; Tao Zhang,2025,IEEE International Joint Conference on Neural Network,,,,,0,0.000,0.000,10.1109/IJCNN64981.2025.11228417,https://www.semanticscholar.org/paper/e78906ad69cacc0cf80b21d27347200c863adb9b,,semantic_scholar,,"Object detection plays a crucial role in various real-world applications, particularly on resource-constrained edge devices. However, existing lightweight detection models often struggle to balance accuracy and computational efficiency due to limitations in fine-grained feature extraction and effect"
579,,Low-power option Greeks: Efficiency-driven market risk analysis using FPGAs,Mark Klaisoongnoen; Nick Brown; O. T. Brown,2022,Heart,,,,,10,0.000,0.000,10.1145/3535044.3535059,https://www.semanticscholar.org/paper/df5d85df5397cc0b89f4bc6da8ec26d6e883a456,https://arxiv.org/pdf/2206.03719,semantic_scholar,,"Quantitative finance is the use of mathematical models to analyse financial markets and securities. Typically requiring significant amounts of computation, an important question is the role that novel architectures can play in accelerating these models. In this paper we explore the acceleration of t"
580,,Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey,Chao Yu; Xuejing Zheng; H. Zhuo; Hai Wan; Weilin Luo,2023,arXiv.org,,,,,10,0.000,0.000,10.48550/arXiv.2304.12090,https://www.semanticscholar.org/paper/28e536d4b425a8743af9b074ddb11baba66f8b47,http://arxiv.org/pdf/2304.12090,semantic_scholar,,"Reinforcement Learning (RL) has achieved tremendous development in recent years, but still faces significant obstacles in addressing complex real-life problems due to the issues of poor system generalization, low sample efficiency as well as safety and interpretability concerns. The core reason unde"
581,,GaaS-X: Graph Analytics Accelerator Supporting Sparse Data Representation using Crossbar Architectures,Nagadastagiri Challapalle; Sahithi Rampalli; Linghao Song; Nandhini Chandramoorthy; Karthik Swaminathan,2020,International Symposium on Computer Architecture,,,,,59,0.000,0.000,10.1109/ISCA45697.2020.00044,https://www.semanticscholar.org/paper/a87f030139dabfac986b0026efa34e2eb443c46a,,semantic_scholar,,"Graph analytics applications are ubiquitous in this era of a connected world. These applications have very low compute to byte-transferred ratios and exhibit poor locality, which limits their computational efficiency on general purpose computing systems. Conventional hardware accelerators employ cus"
582,,A μ-NMC-Δ-IMC Heterogeneous STT-MRAM Compute-in-Memory Macro Using Δ-Clamping Bit Reduction for Noise-Tolerant Bayesian Neural Networks,De-Qi You; W. Khwa; Bo Zhang; Fang-Yi Chen; Andrew Lee,2026,IEEE Journal of Solid-State Circuits,,,,,0,0.000,0.000,10.1109/JSSC.2025.3617770,https://www.semanticscholar.org/paper/820b0eb77923dbbb14b0aa13429659de712eb306,,semantic_scholar,,Nonvolatile compute-in-memory (nvCIM) macros integrate memory and computation to enable high-density multiply-and-accumulate (MAC) acceleration for inference tasks on low-power edge artificial intelligence (AI) devices. Bayesian neural networks (BNNs)—which represent weights with mean (<inline-formu
583,,FOG EDGE COMPUTING: Enhancing Performance and Efficiency with the GRB Method,Sushil Prabhu Prabhakaran,2024,SOJ Materials Science &amp; Engineering,,,,,0,0.000,0.000,10.15226/sojmse.2024.00182,https://www.semanticscholar.org/paper/dd389bd715b14c34c940dbc171feb4a91b187abe,https://doi.org/10.15226/sojmse.2024.00182,semantic_scholar,,"Abstract: The emerging paradigm of fog edge computing brings the capabilities of the cloud closer to the edge of the network, effectively addressing
the requirements for real-time data processing and low-latency applications. By deploying computational resources and services at the network’s edge,
f"
584,,DeepSeek-VL: Towards Real-World Vision-Language Understanding,Haoyu Lu; Wen Liu; Bo Zhang; Bing-Li Wang; Kai Dong,2024,arXiv.org,,,,,631,0.000,0.000,10.48550/arXiv.2403.05525,https://www.semanticscholar.org/paper/b14e5138d4d1f3577b2390541dc7b730a41bb651,,semantic_scholar,,"We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Our approach is structured around three key dimensions: We strive to ensure our data is diverse, scalable, and extensively covers real-world scenarios including w"
585,,The Influence of 3D Motions on the Efficiency of Children’s Indoor Evacuations,Ruihang Xie; S. Zlatanova; J. Lee,2025,"ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences",,,,,0,0.000,0.000,10.5194/isprs-annals-x-4-w6-2025-233-2025,https://www.semanticscholar.org/paper/3c6aca45ad1dcf2fb8faf17843b4dc9624ae025c,,semantic_scholar,,"Abstract. During emergency evacuations, children sometimes adopt three-dimensional (3D) motions, such as crawling close to the ground or climbing up/down to obstacles, to pass through restricted spaces or in situations of heightened urgency. Examining how these motions affect children’s evacuation p"
586,,Multi-Scale Representation Learning for Image Restoration with State-Space Model,Yuhong He; Long Peng; Qiaosi Yi; Chen Wu; Lu Wang,2024,arXiv.org,,,,,7,0.000,0.000,10.48550/arXiv.2408.10145,https://www.semanticscholar.org/paper/1a2e82e4315e241e7110119df3b1f4d173243bb3,,semantic_scholar,,"Image restoration endeavors to reconstruct a high-quality, detail-rich image from a degraded counterpart, which is a pivotal process in photography and various computer vision systems. In real-world scenarios, different types of degradation can cause the loss of image details at various scales and d"
587,,Efficient Large Graph Processing with Chunk-Based Graph Representation Model,Rui Wang; Weixu Zong; Shuibing He; Xinyu Chen; Zhenxin Li,2024,USENIX Annual Technical Conference,,,,,6,0.000,0.000,,https://www.semanticscholar.org/paper/12ed48a79fbd8a945c32578e4f9244b0e1ec6d51,,semantic_scholar,,
588,,CrossJEPA: Cross-Modal Joint-Embedding Predictive Architecture for Efficient 3D Representation Learning from 2D Images,Avishka Perera; Kumal Hewagamage; Saeedha Nazar; Kavishka Abeywardana; Hasitha Gallella,2025,,,,,,0,0.000,0.000,,https://www.semanticscholar.org/paper/53275298f41a74e0d2395c6d96bc21cbd9d02d26,,semantic_scholar,,"Image-to-point cross-modal learning has emerged to address the scarcity of large-scale 3D datasets in 3D representation learning. However, current methods that leverage 2D data often result in large, slow-to-train models, making them computationally expensive and difficult to deploy in resource-cons"
589,,Accelerating Small Language Model via Quantization: A GPT-4 Guided Approach for Low-Resource Story Completion,Rakshit Dabral; Dr. Archana Kumar,2025,INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT,,,,,0,0.000,0.000,10.55041/ijsrem53280,https://www.semanticscholar.org/paper/5fe490b29038beacdfe46680ff4fe31cf7c7b9ed,,semantic_scholar,,"Abstract- This paper introduces Story Completer, a sophisticated and efficient engine for real-time children's story completion, extending the foundational work of the TinyStories project. While TinyStories demonstrated that small models (<10M parameters) can generate coherent narratives on simplifi"
590,,"LiteMixer: Scalable, Low-Overhead Multi-Scale Mixing for Time Series Forecasting",Issam Ait Yahia; Abdelkader El Mahdaouy; Soufiane Oualil; Ismail Berrada,2025,International Conference on Wireless Networks and Mobile Communications,,,,,0,0.000,0.000,10.1109/WINCOM65874.2025.11313463,https://www.semanticscholar.org/paper/f1cf16fe373d8fbc0f9739e5c2ba947f06c7c2a3,,semantic_scholar,,
591,,ELLIE: Energy-Efficient LLM Inference at the Edge Via Prefill-Decode Splitting,Haoyang Fan; Yi-Chien Lin; Viktor K. Prasanna,2025,"IEEE International Conference on Application-Specific Systems, Architectures, and Processors",,,,,2,0.000,0.000,10.1109/ASAP65064.2025.00031,https://www.semanticscholar.org/paper/0827b6ab8db1b1cccfdb0d6469231cbb5febfe5b,,semantic_scholar,,"As Large Language Models (LLMs) are increasingly deployed for on-device applications, optimizing inference on edge platforms becomes critical. In real-world scenarios, LLM inference must satisfy diverse constraints and user requirements, such as low latency, high energy efficiency, or low Energy-Del"
592,,Experimental and Computational Investigations of the Thermal Environment in a Small Operational Data Center for Potential Energy Efficiency Improvements,Ismail Turkmen; Cem Ahmet Mercan; H. Erden,2020,,,,,,4,0.000,0.000,10.1115/1.4047845,https://www.semanticscholar.org/paper/01078e00c1f4ef161c9a057a6d7079a2de577b74,,semantic_scholar,,"
 The share of equipment and power use in smaller data centers (DCs) is comparable with that of more massive counterparts. However, they grabbed less attention in the literature despite being less energy-efficient. This study highlights the challenges of setting up a computational fluid dynamics (CF"
593,,SHAP values via sparse Fourier representation,Ali Gorji; Andisheh Amrollahi; Andreas Krause,2024,,,,,,2,0.000,0.000,,https://www.semanticscholar.org/paper/7ee42892d7798651d3bf3fad17268ba47db29fcf,,semantic_scholar,,SHAP (SHapley Additive exPlanations) values are a widely used method for local feature attribution in interpretable and explainable AI. We propose an efficient two-stage algorithm for computing SHAP values in both black-box setting and tree-based models. Motivated by spectral bias in real-world pred
594,,Spatiotemporal Spectrum Neural Network for Low-SNR Communication Signal Detection,Le Cheng; Yue Liu; Zhengliang Hu; Hongna Zhu; Bin Luo,2026,IEEE Transactions on Cognitive Communications and Networking,,,,,0,0.000,0.000,10.1109/TCCN.2025.3565950,https://www.semanticscholar.org/paper/7b5db6b6eb45378981f41f27659c0e2d8e269611,,semantic_scholar,,"Detecting wireless communication signals in low signal-to-noise ratio (SNR) environments is challenging due to noise interference and frequency overlap. Traditional array processing techniques rely on direction-of-arrival (DOA) estimation and beamforming before detection and recognition, often resul"
595,,Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting,Yuang Zhao; Tianyu Li; Jiadong Chen; Shenrong Ye; Fuxin Jiang,2024,arXiv.org,,,,,2,0.000,0.000,10.48550/arXiv.2411.17257,https://www.semanticscholar.org/paper/bac5e80463d6d37d6a6f25d657797d52f90f11d2,,semantic_scholar,,"Industry 5.0 introduces new challenges for Long-term Time Series Forecasting (LTSF), characterized by high-dimensional, high-resolution data and high-stakes application scenarios. Against this backdrop, developing efficient and interpretable models for LTSF becomes a key challenge. Existing deep lea"
596,,FERMixNet: An Occlusion Robust Facial Expression Recognition Model With Facial Mixing Augmentation and Mid-Level Representation Learning,Yansong Huang; Junjie Peng; Wenqiang Zhang; Tong Zhao; Gan Chen,2025,IEEE Transactions on Affective Computing,,,,,8,0.000,0.000,10.1109/TAFFC.2024.3454102,https://www.semanticscholar.org/paper/2457814bc97d12f98c38d18fd936c06df1dabe65,,semantic_scholar,,"Facial expressions can provide a better understanding of people’s mental status and attitudes towards specific things. However, facial occlusion in real world is an unfavorable phenomenon that greatly affects the performance of facial expression recognition models. Recent works addressing the occlus"
597,,Multi-scale Unified Network for Image Classification,Wenzhuo Liu; Fei Zhu; Cheng-Lin Liu,2024,arXiv.org,,,,,1,0.000,0.000,10.48550/arXiv.2403.18294,https://www.semanticscholar.org/paper/9b6cc5b2c2b646a07f32752fd406cabd0ecfca6f,,semantic_scholar,,"Convolutional Neural Networks (CNNs) have advanced significantly in visual representation learning and recognition. However, they face notable challenges in performance and computational efficiency when dealing with real-world, multi-scale image inputs. Conventional methods rescale all input images "
598,,AI-Driven Computational Frameworks: Advancing Edge Intelligence and Smart Systems,G. Prabaharan; S. Vidhya; T. Chithrakumar; K. Sika; M.Balakrishnan,2025,International Journal of Computational and Experimental Science and Engineering,,,,,13,0.000,0.000,10.22399/ijcesen.1165,https://www.semanticscholar.org/paper/58aa72fb077c5f96b4dd56a6c80a9256c985c10a,https://doi.org/10.22399/ijcesen.1165,semantic_scholar,,"The rapid advancements in Artificial Intelligence (AI) and Edge Computing are transforming modern computing paradigms by enabling real-time processing, low-latency decision-making, and enhanced intelligence in smart systems. This paper presents an AI-driven computational framework that integrates Ed"
599,,Multi-scale adaptive low-light image enhancement based on deep learning,Taotao Cao; Taile Peng; Hao Wang; Xiaotong Zhu; Jia Guo,2024,J. Electronic Imaging,,,,,1,0.000,0.000,10.1117/1.JEI.33.4.043033,https://www.semanticscholar.org/paper/498e6ed54e20d75e0a007cf6465c70270ce4b037,,semantic_scholar,,"Abstract. Existing low-light image enhancement (LLIE) technologies have difficulty balancing image quality and computational efficiency. In addition, they amplify the noise and artifacts of the original image when enhancing deep dark images. Therefore, this study proposes a multi-scale adaptive low-"
600,,Enhancing generalizability and performance in drug–target interaction identification by integrating pharmacophore and pre-trained models,Zuolong Zhang; Xin He; Dazhi Long; Gang Luo; Shengbo Chen,2024,Bioinform.,,,,,4,0.000,0.000,10.1093/bioinformatics/btae240,https://www.semanticscholar.org/paper/38cae834827755fe52cdc2576ba9cfde2dc9d11b,https://academic.oup.com/bioinformatics/article-pdf/40/Supplement_1/i539/58355122/btae240.pdf,semantic_scholar,,"Abstract Motivation In drug discovery, it is crucial to assess the drug–target binding affinity (DTA). Although molecular docking is widely used, computational efficiency limits its application in large-scale virtual screening. Deep learning-based methods learn virtual scoring functions from labeled"
601,,HyperT5: Towards Compute-Efficient Korean Language Modeling,Dongju Park; Soonwon Ka; Kang Min Yoo; Gichang Lee; Jaewoo Kang,2023,Annual Meeting of the Association for Computational Linguistics,,,,,0,0.000,0.000,10.18653/v1/2023.acl-industry.40,https://www.semanticscholar.org/paper/789ccb1c15919fee66f1b2b67dc40365cb9996dd,https://aclanthology.org/2023.acl-industry.40.pdf,semantic_scholar,,"Pretraining and fine-tuning language models have become the standard practice in industrial natural language processing (NLP), but developing and deploying general-purpose language models without the abundant computation or data resources is a real-world issue faced by smaller organizations or commu"
602,,Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices,Tasnim Shahriar,2025,arXiv.org,,,,,7,0.000,0.000,10.48550/arXiv.2505.03303,https://www.semanticscholar.org/paper/4d08b00cd14ed2963e2ce561e73df30b72a4e511,,semantic_scholar,,"This paper presents a comprehensive evaluation of lightweight deep learning models for image classification, emphasizing their suitability for deployment in resource-constrained environments such as low-memory devices. Five state-of-the-art architectures - MobileNetV3 Small, ResNet18, SqueezeNet, Ef"
603,,"Real World Assets on-Chain Assistance Low-Altitude Computility Networks: Architecture, Methodology, and Challenges",Haoxiang Luo; Ruichen Zhang; Yinqiu Liu; Gang Sun; Hongfang Yu,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2508.17911,https://www.semanticscholar.org/paper/2f31b5a1a162b38730be0c1c330f10aef05efdbc,,semantic_scholar,,"Low-altitude airspace is becoming a new frontier for smart city services and commerce. Networks of drones, electric Vertical Takeoff and Landing (eVTOL) vehicles, and other aircraft, termed Low-Altitude Economic Networks (LAENets), promise to transform urban logistics, aerial sensing, and communicat"
604,,A Review of Research on Dense Matching Algorithms in Digital Surface Model,Ziti Zhang; Wang Chang; Fan Mo; Gan Mao; Gang Chen,2025,"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",,,,,0,0.000,0.000,10.5194/isprs-archives-xlviii-4-w14-2025-429-2025,https://www.semanticscholar.org/paper/548e3c44e17bcedc795ad23f6c8bfa03cef79a51,,semantic_scholar,,"Abstract. Digital Surface Models (DSM), critical for 3D surface representation, rely on dense matching algorithms for accuracy and efficiency. This review examines two decades of advancements in feature-based, region-based, and deep learning-driven methods. Feature-based methods such as SIFT and ORB"
605,,TinyFaceDL Lightweight Transformer CNN Hybrid Model for Face Recognition on Low Power IoT and Edge Devices,G. Ramkumar; Ahmad Al-qerem; G. Kalyani; A. Vamsi; Devolla Manogna,2025,2025 7th International Conference on Innovative Data Communication Technologies and Application (ICIDCA),,,,,0,0.000,0.000,10.1109/ICIDCA66325.2025.11280537,https://www.semanticscholar.org/paper/3e827baf3b51d3e1b41dc4fd9cbae2055a246cf4,,semantic_scholar,,"Detection of faces on low-power Internet of Things (IoT) and edge computing devices is a very much challenging task due to the limitation of less computational resources, limited energy, and other environmental factors including illumination, occlusion, and pose changes. In response to these difficu"
606,,Optimizing Deep Learning Models through Spatial Attentive Architectural Enhancements and Binarization Techniques,Bishnu Pada Saha; Satya Ranjan Dash; Mainak Bandyopadhyay; Paola Barra; Vinh Truong Hoang,2025,Educational Sciences International Conference,,,,,0,0.000,0.000,10.1109/ESIC64052.2025.10962698,https://www.semanticscholar.org/paper/1d677224a1c0679ea1a1d5360688c819141f57a8,,semantic_scholar,,Attention mechanisms in vision applications of the computer world dynamically adjust feature weights to amplify the model’s capability to perceive information. This adaptive recalibration improves the overall effectiveness of the model. Spatial attention has seen widespread use to boost the efficien
607,,Seismic vulnerability signal analysis of low tower cable-stayed bridges method based on convolutional attention network,Dingbo Chen; Liangjun Lai,2024,Nonlinear Engineering,,,,,0,0.000,0.000,10.1515/nleng-2022-0336,https://www.semanticscholar.org/paper/c786d43316c0d5b2bf6d55f032e5868ab9d7dce5,https://www.degruyter.com/document/doi/10.1515/nleng-2022-0336/pdf,semantic_scholar,,"Abstract Due to the particularity and complexity of sedimentary environments, the wave impedance differences between different reflection interfaces in underground media may vary greatly. Therefore, an encoder–decoder neural network is proposed to enhance erroneous seismic weak reflection signals. T"
608,,Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection,Daihong Jiang; Zhixiang Chen; Sanyou Zhang; Yunfei Li; Lu Zhao,2025,IEEE Access,,,,,1,0.000,0.000,10.1109/ACCESS.2025.3596642,https://www.semanticscholar.org/paper/369efca7b80e68e7cbd9ac411ba29d05bdc06b5a,,semantic_scholar,,"Low-rank optimization plays a pivotal role in image processing due to its inherent ability to capture low-dimensional structures and promote sparsity. Traditional low-rank decomposition methods aim to recover low-rank components and isolate sparse elements, but the structural integrity of the sparse"
609,,An Efficiency Optimization Study of Data Governance Legal Issues in the Framework of Privacy Computing,Fei Hu; Tingting Chen,2024,Applied Mathematics and Nonlinear Sciences,,,,,0,0.000,0.000,10.2478/amns-2024-2833,https://www.semanticscholar.org/paper/1b6776e23da796b4f326c52192a66ed5851d944e,https://doi.org/10.2478/amns-2024-2833,semantic_scholar,,Abstract The rapid development of technologies such as big data and cloud computing provides convenience for people’s production and life but also brings hidden dangers for personal privacy. The study clarifies the legal norms and guarantees of personal information protection (privacy) in countries 
610,,Triplet Attention Transformer for Spatiotemporal Predictive Learning,Xuesong Nie; Xi Chen; Haoyuan Jin; Zhihang Zhu; Yunfeng Yan,2023,IEEE Workshop/Winter Conference on Applications of Computer Vision,,,,,15,0.000,0.000,10.1109/WACV57701.2024.00688,https://www.semanticscholar.org/paper/c23b6fc995cdfcd23230f20edde64837f4615bd9,https://arxiv.org/pdf/2310.18698,semantic_scholar,,"Spatiotemporal predictive learning offers a self-supervised learning paradigm that enables models to learn both spatial and temporal patterns by predicting future sequences based on historical sequences. Mainstream methods are dominated by recurrent units, yet they are limited by their lack of paral"
611,,Efficient compression of reduced impedance matrices for trimmed structural models: a novel methodology and industrial validation,Andre Antonio ANDRADE PAIVA; Benoit Van den Nieuwenhof; G. Lielens; Julien Verhaegen; Jeremy Charbonneau,2024,INTER-NOISE and NOISE-CON Congress and Conference Proceedings,,,,,1,0.000,0.000,10.3397/in_2024_3609,https://www.semanticscholar.org/paper/2b76b48c2f98300e3c5ea55c72ebcae26a61facd,,semantic_scholar,,"In response to increasingly strict vibration and noise regulations, software frameworks such as Nastran and Actran have stepped up to the challenge, providing sophisticated solutions to efficiently model damping treatments within numerical methods. One of the available techniques is
 the representat"
612,,Enhancing seismic risk assessment through probabilistic analysis of liquefaction potential index: a computational intelligence approach,S. Ghani; Sunita Kumari; A. K. Choudhary,2025,Geomechanics and Geoengineering,,,,,0,0.000,0.000,10.1080/17486025.2025.2452624,https://www.semanticscholar.org/paper/44e66de868a47c9434e73219e5ec7d9823821013,,semantic_scholar,,ABSTRACT This study proposes a novel computational intelligence approach for enhancing seismic risk assessment through probabilistic analysis of the liquefaction potential index (LPI). The methodology leverages a hybridised model that combines backpropagation neural networks (BcNN) with an improved 
613,,"Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions",Ismail Lamaakal; Yassine Maleh; Khalid El Makkaoui; Ibrahim Ouahbi; Paweł Pławiak,2025,Italian National Conference on Sensors,,,,,28,0.000,0.000,10.3390/s25051318,https://www.semanticscholar.org/paper/174828b817d0d0671e2b9a368fb01b17971487c5,https://doi.org/10.3390/s25051318,semantic_scholar,,"Large Language Models (LLMs), like GPT and BERT, have significantly advanced Natural Language Processing (NLP), enabling high performance on complex tasks. However, their size and computational needs make LLMs unsuitable for deployment on resource-constrained devices, where efficiency, speed, and lo"
614,,Evaluate the numerical models’ performance in the Nile River,Fatma Samir,2024,ISH Journal of Hydraulic Engineering,,,,,2,0.000,0.000,10.1080/09715010.2024.2394796,https://www.semanticscholar.org/paper/f78e012c0b194293cfe391ad8a5aae41ddce0f03,,semantic_scholar,,"ABSTRACT To study the water management of natural rivers, two-dimensional (2D) hydrodynamic models have become essential tools. The performance of five different hydrodynamic modelling packages, SRH 2D (developed by U.S. Bureau of Reclamation), Delft 3D (developed by Deltares), FESWMS (developed by "
615,,AugGKG: a grid-augmented geographic knowledge graph representation and spatio-temporal query model,Bing Han; Tengteng Qu; Xiaochong Tong; Haipeng Wang; Hao Liu,2023,International Journal of Digital Earth,,,,,9,0.000,0.000,10.1080/17538947.2023.2290569,https://www.semanticscholar.org/paper/c5bcb6a63a49bc5ea116d6d7f6ee977aadae591f,https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2290569?needAccess=true,semantic_scholar,,"ABSTRACT As an emerging knowledge representation model in the domain of knowledge graphs, geographic knowledge graph can take full advantage of semantic, spatial and temporal information to facilitate answering spatio-temporal questions and completing relations. However, the representation of geogra"
616,,Edge AI for Real-Time Object Tracking in Dynamic Environments using Hybrid Motion Estimation Models,Hassan Muhamed Ale; Akhilesh Pahade; D. Anandhasilambarasan; N. M. Shrirao; Gangadharan Rajappa Sakthidharan,2025,2025 International Conference on Metaverse and Current Trends in Computing (ICMCTC),,,,,0,0.000,0.000,10.1109/ICMCTC62214.2025.11196234,https://www.semanticscholar.org/paper/9481598f5405ea648befc74747df336ac323e86a,,semantic_scholar,,"In applications such as autonomous vehicles, surveillance, they need real-time object tracking in a dynamic environment. However, traditional motion estimation techniques are not accurate and are not easy to adapt, while deep learning-based models usually need high computational power, which is not "
617,,Fine-Tuning Small LLMs for High-Quality Semantic Search: A Cost-Efficient Alternative to Foundation Models,Puripanda SHARAT CHANDRA,2025,INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT,,,,,0,0.000,0.000,10.55041/ijsrem49678,https://www.semanticscholar.org/paper/cc10eae92743df4a1978b2bb5fb25e2c3d7f848f,,semantic_scholar,,"Abstract - Large language models (LLMs) have demonstrated remarkable performance in natural language understanding, yet their deployment for real-time semantic search and recommendation tasks remains impractical due to significant computational demands. This paper introduces a cost-efficient framewo"
618,,Med-GRIM: Enhanced Zero-Shot Medical VQA using prompt-embedded Multimodal Graph RAG,Rakesh Raj Madavan; Akshat Kaimal; Hashim Faisal; Chandrakala Shanmuganathan,2025,arXiv.org,,,,,1,0.000,0.000,10.48550/arXiv.2508.06496,https://www.semanticscholar.org/paper/43f766c034e12bc4fdc25be5c3fb7064e5e54e2b,,semantic_scholar,,"An ensemble of trained multimodal encoders and vision-language models (VLMs) has become a standard approach for visual question answering (VQA) tasks. However, such models often fail to produce responses with the detailed precision necessary for complex, domain-specific applications such as medical "
619,,Real-World Multi-View Stereo via Learning RGB-D Structural Consistency From Depth Super-Resolution,Yimei Liu; Jingchao Cao; H. Fan; Junyu Dong; Sheng Chen,2025,IEEE transactions on circuits and systems for video technology (Print),,,,,0,0.000,0.000,10.1109/TCSVT.2025.3571940,https://www.semanticscholar.org/paper/bbb7e4d59cb3acd47b69ee728114cf84ea8eaf0d,,semantic_scholar,,"Learning-based Multi-View Stereo (MVS) methods, typically reliant on cascaded cost volume formulations, perform well on small-scale scenes. However, as the depth range of captured images becomes broader and more varied, the coarse-to-fine depth sampling process, which depends solely on feature match"
620,,"Efficient Hyperdimensional Learning with Trainable, Quantizable, and Holistic Data Representation",Jiseung Kim; Hyun-Soo Lee; M. Imani; Yeseong Kim,2023,"Design, Automation and Test in Europe",,,,,9,0.000,0.000,10.23919/DATE56975.2023.10137134,https://www.semanticscholar.org/paper/62c7307181522cd589778d1527ed46ed4fca05f1,,semantic_scholar,,"Hyperdimensional computing (HDC) is a computing paradigm that draws inspiration from human memory models. It represents data in the form of high-dimensional vectors. Recently, many works in literature have tried to use HDC as a learning model due to its simple arithmetic and high efficiency. However"
621,,Data-driven methods to estimate the committor function in conceptual ocean models,Valérian Jacques-Dumas; René M. van Westen; F. Bouchet; H. Dijkstra,2023,Nonlinear Processes in Geophysics,,,,,19,0.000,0.000,10.5194/npg-30-195-2023,https://www.semanticscholar.org/paper/79266efed353971951adf628bb0bb1e002d3e809,https://npg.copernicus.org/articles/30/195/2023/npg-30-195-2023.pdf,semantic_scholar,,"Abstract. In recent years, several climate subsystems have been identified that may undergo a relatively rapid transition compared to the changes in their forcing. Such transitions are rare events in general, and simulating long-enough trajectories in order to gather sufficient data to determine tra"
622,,Optimizing Energy Consumption through Scheduling in Low-resource Edge Clusters using Multi-agent PPO,Hippolyte Verninas; Leonardo Linguaglossa,2024,StudentWorkshop@CoNEXT,,,,,0,0.000,0.000,10.1145/3694812.3699928,https://www.semanticscholar.org/paper/b7ed1942b5ea822b939284500a199765dc1a571b,,semantic_scholar,,"With the growing demand for computing resources, data centers must optimize energy consumption while maintaining performance. This paper focuses on optimizing job scheduling in low-resource edge clusters using Multi-Agent Proximal Policy Optimization (MAPPO). Cloud computing offers scalability and f"
623,,Streamlining Disaster Detection: A Lightweight Fusion Architecture for Low-Resource Deployment,Marwen Bouabid; Mohamed Farah,2024,ACS/IEEE International Conference on Computer Systems and Applications,,,,,0,0.000,0.000,10.1109/AICCSA63423.2024.10912524,https://www.semanticscholar.org/paper/e13ed0162d19f768f61335e0a7b995d19d029c3e,,semantic_scholar,,"Deep learning has revolutionized crisis identification across various domains, driving significant advancements in artificial intelligence. However, the high computational demands of these models present challenges for deployment on low-resource devices. In this paper, we present a lightweight versi"
624,,High-performance solutions of geographically weighted regression in R,Binbin Lu; Yigong Hu; D. Murakami; C. Brunsdon; A. Comber,2022,Geo-Spatial Information Science,,,,,28,0.000,0.000,10.1080/10095020.2022.2064244,https://www.semanticscholar.org/paper/c6527f8da91a0943e88b7ab172f5b65ee24c36fa,https://eprints.whiterose.ac.uk/187198/11/High%20performance%20solutions%20of%20geographically%20weighted%20regression%20in%20R.pdf,semantic_scholar,,"ABSTRACT As an established spatial analytical tool, Geographically Weighted Regression (GWR) has been applied across a variety of disciplines. However, its usage can be challenging for large datasets, which are increasingly prevalent in today’s digital world. In this study, we propose two high-perfo"
625,,EnrichRBP: an automated and interpretable computational platform for predicting and analysing RNA-binding protein events,Yubo Wang; Haoran Zhu; Yansong Wang; Yuning Yang; Yujian Huang,2025,Bioinformatics,,,,,1,0.000,0.000,10.1093/bioinformatics/btaf018,https://www.semanticscholar.org/paper/bb3df7b64e86e6540342247231220b35e75ab651,https://doi.org/10.1093/bioinformatics/btaf018,semantic_scholar,,"Abstract Motivation Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA. Re"
626,,WavJEPA: Semantic learning unlocks robust audio foundation models for raw waveforms,Goksenin Yuksel; Pierre Guetschel; Michael Tangermann; M. Gerven; Kiki van der Heijden,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2509.23238,https://www.semanticscholar.org/paper/d0d5693107cfcc199e7c02986a17306dea5ce115,,semantic_scholar,,"Learning audio representations from raw waveforms overcomes key limitations of spectrogram-based audio representation learning, such as the long latency of spectrogram computation and the loss of phase information. Yet, while self-supervised speech representation learning from raw waveforms has been"
627,,Early Colon Cancer Prediction from Histopathological Images Using Enhanced Deep Learning with Confidence Scoring,V. P. G. Pushparathi; J. Shajeena; T. Kamalam; M. Revathi,2025,Cancer Investigation,,,,,1,0.000,0.000,10.1080/07357907.2025.2483302,https://www.semanticscholar.org/paper/61f81f7e139ccb9c9cd32a781633e03c14902f0c,,semantic_scholar,,"Abstract Colon Cancer (CC) arises from abnormal cell growth in the colon, which severely impacts a person’s health and quality of life. Detecting CC through histopathological images for early diagnosis offers substantial benefits in medical diagnostics. This study proposes NalexNet, a hybrid deep-le"
628,,Scalable Reachset-Conformant Identification of Linear Systems,Laura Lützow; Matthias Althoff,2024,IEEE Control Systems Letters,,,,,8,0.000,0.000,10.1109/LCSYS.2024.3397058,https://www.semanticscholar.org/paper/ad1d93f81d10bafe9842baed2c9d061cb588065d,https://ieeexplore.ieee.org/ielx7/7782633/7912304/10520655.pdf,semantic_scholar,,"By monitoring the set of reachable outputs, safety can be verified. However, to compute the reachable set of real-world systems, we require models that are able to produce all possible system behaviors. These kinds of models are called reachset-conformant, and their identification is a promising new"
629,,FSID: a novel approach to human activity recognition using few-shot weight imprinting,Mohammad Belal; Taimur Hassan; Abdelfatah Hassan; Divya Velayudhan; Noureldin Elhendawi,2025,Scientific Reports,,,,,3,0.000,0.000,10.1038/s41598-025-04323-7,https://www.semanticscholar.org/paper/df88e8366ed1b3707680456d1032302b1caa1fbe,,semantic_scholar,,"Accurate recognition of human activities from gait sensory data plays a vital role in healthcare and wellness monitoring. However, conventional deep learning models for Human Activity Recognition (HAR) often require large labeled datasets and extensive training, which limits their effectiveness in r"
630,,4D Facial Avatar Reconstruction From Monocular Video via Efficient and Controllable Neural Radiance Fields,Jeong-gi Kwak; Hanseok Ko,2024,IEEE Access,,,,,2,0.000,0.000,10.1109/ACCESS.2024.3355052,https://www.semanticscholar.org/paper/784459e77aacc1c69599405ca2e0bea9e1047a03,https://ieeexplore.ieee.org/ielx7/6287639/6514899/10401911.pdf,semantic_scholar,,"We present an efficient approach for monocular 4D facial avatar reconstruction using a dynamic neural radiance field (NeRF). Over the years, NeRFs have been popular methods for 3D scene representation, but lack computational efficiency and controllabilty, thus it is impractical for real world applic"
631,,Optimized Fixed Point MAC Unit for Neural Network on FPGA,Farshideh Kordi; Paul Fortier; A. Miled,2024,International Congress of Mathematicans,,,,,2,0.000,0.000,10.1109/ICM63406.2024.10815828,https://www.semanticscholar.org/paper/82f3e7a2f1cc173032b57bf662e9891055e8db7b,,semantic_scholar,,"In recent years, the demand for efficient deep learning models has accelerated the exploration of low-precision data representations that maintain competitive accuracy levels. Among these, Q-format fixed-point arithmetic stands out as a highly effective approach for implementing low-precision format"
632,,Transformer-based code model with compressed hierarchy representation,Kechi Zhang; Jia Li; Zhuo Li; Zhi Jin; Ge Li,2025,Empirical Software Engineering,,,,,1,0.000,0.000,10.1007/s10664-025-10612-6,https://www.semanticscholar.org/paper/7278d68b7ff0f5e353a1adc1390c5bd59b09b294,,semantic_scholar,,
633,,When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling,Yalan Song; W. Knoben; Martyn P. Clark; D. Feng; K. Lawson,2024,Hydrology and Earth System Sciences,,,,,21,0.000,0.000,10.5194/hess-28-3051-2024,https://www.semanticscholar.org/paper/3935221db2083cc7529924311994f9edbb9635ee,,semantic_scholar,,"Abstract. Recent advances in differentiable modeling, a genre of physics-informed machine learning that trains neural networks (NNs) together with process-based equations, have shown promise in enhancing hydrological models' accuracy, interpretability, and knowledge-discovery potential. Current diff"
634,,Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptation,Tran Tuan Kiet; Nguyen Thang Loi; Vo Nguyen Le Duy,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2508.07049,https://www.semanticscholar.org/paper/34709e80399c844b999bd743213b63e172520aff,,semantic_scholar,,"Anomaly detection (AD) plays a vital role across a wide range of domains, but its performance might deteriorate when applied to target domains with limited data. Domain Adaptation (DA) offers a solution by transferring knowledge from a related source domain with abundant data. However, this adaptati"
635,,Linking Frequentist and Bayesian Change-Point Methods,David Ardia; A. Dufays; C. O. Criado,2023,Journal of Business &amp; Economic Statistics,,,,,0,0.000,0.000,10.1080/07350015.2023.2293166,https://www.semanticscholar.org/paper/5a65ad77395ee261ed4de47caf503e31359dba01,https://arxiv.org/pdf/2306.05265,semantic_scholar,,Abstract We show that the two-stage minimum description length (MDL) criterion widely used to estimate linear change-point (CP) models corresponds to the marginal likelihood of a Bayesian model with a specific class of prior distributions. This allows results from the frequentist and Bayesian paradi
636,,Probabilistic photonic computing for AI,Frank Brückerhoff-Plückelmann; A. Ovvyan; Akhil Varri; Hendrik Borras; Bernhard Klein,2025,Nature Computational Science,,,,,7,0.000,0.000,10.1038/s43588-025-00800-1,https://www.semanticscholar.org/paper/52c797c2d91cb81f282a0f875b8a0d9bf86cc3ab,,semantic_scholar,,
637,,Field‐programmable gate array acceleration of the Tersoff potential in LAMMPS,Quan Deng; Qiang Liu,2025,,,,,,7,0.000,0.000,10.1002/eng2.12694,https://www.semanticscholar.org/paper/7ea4487b0f9777dd61d5e4310897c379f3e01003,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/eng2.12694,semantic_scholar,,"Molecular dynamics simulation is a common method to help humans understand the microscopic world. The traditional general‐purpose high‐performance computing platforms are hindered by low computational and power efficiency, constraining the practical application of large‐scale and long‐time many‐body"
638,,Subgrid corrections for the linear inertial equations of a compound flood model – a case study using SFINCS 2.1.1 Dollerup release,M. van Ormondt; T. Leijnse; Roel J. A. de Goede; Kees Nederhoff; A. V. van Dongeren,2025,Geoscientific Model Development,,,,,5,0.000,0.000,10.5194/gmd-18-843-2025,https://www.semanticscholar.org/paper/2e51239e72f3df3e73d1ccc3523ef4ea7b3144eb,,semantic_scholar,,"Abstract. Accurate flood risk assessments and early warning systems are needed to protect and prepare people in coastal areas from storms. In order to provide this information efficiently and on time, computational costs in flood models need to be kept as low as possible. One way to achieve this goa"
639,,AtlasGS: Atlanta-world Guided Surface Reconstruction with Implicit Structured Gaussians,Xiyu Zhang; Chong Bao; Yipeng Chen; Hongjia Zhai; Yitong Dong,2025,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2510.25129,https://www.semanticscholar.org/paper/fa3b002fc889284720baaf77752eee1c7e3380cc,,semantic_scholar,,"3D reconstruction of indoor and urban environments is a prominent research topic with various downstream applications. However, existing geometric priors for addressing low-texture regions in indoor and urban settings often lack global consistency. Moreover, Gaussian Splatting and implicit SDF field"
640,,Evaluating the E3SMv2-MPAS ocean–sea ice coupled unstructured model in the Arctic: Atlantification processes and systematic biases,Xinyuan Lv; Huizan Wang; Yu Cao; Kaijun Ren; Yangjun Wang,2025,Geoscientific Model Development,,,,,0,0.000,0.000,10.5194/gmd-18-8535-2025,https://www.semanticscholar.org/paper/3d6396f2902dbaa5255d3ce1b97d0490b40d4d1a,,semantic_scholar,,Abstract. Advancing high-resolution Arctic ocean–sea ice modeling is critical for understanding polar amplification and improving climate projections but faces challenges from computational limits and cross-scale interactions. The simulation capabilities of the ocean–sea ice coupled model (E3SMv2-MP
641,,A Novel Off-Grid Model and Fast Iterative Method for DOA Estimation With Arbitrary Arrays,Chunlei Zhao; Jiarong Yao; Xuhui Li; Jingxiao Li; Juan Li,2024,"2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)",,,,,0,0.000,0.000,10.1109/ICSIDP62679.2024.10868702,https://www.semanticscholar.org/paper/1ac2bbe2653b0f7c4adeaa587f7904ca4c8772e7,,semantic_scholar,,"High accuracy and low computational complexity are always contradictory for any grid-based DOA estimators. To overcome such difficulty, we establish a novel off-gird model based on approximated linear representation of continuous steering vector space, and propose an estimator based on grid location"
642,,Research on Improved Particle Swarm Computational Intelligence Algorithm and Its Application to Multi-Objective Optimisation,Lifei Chen; Fang Xiong,2024,Applied Mathematics and Nonlinear Sciences,,,,,1,0.000,0.000,10.2478/amns-2024-1440,https://www.semanticscholar.org/paper/3fd97a19cbbea762e6bf1e71b7354d3fe8a40a47,https://sciendo.com/pdf/10.2478/amns-2024-1440,semantic_scholar,,"Abstract Due to the pervasive generalization challenges in optimization technology, there is a noticeable trend toward planning and diversifying optimization techniques. This paper focuses on particle swarm optimization algorithms, particularly their application in multi-objective optimization scena"
643,,A new computationally efficient algorithm to generate global fractional vegetation cover from Sentinel-2 imagery at 10 m resolution,Xu Ma; Jianli Ding; Hui Sun; Lei Lu; Xiao Cheng,2024,International Journal of Digital Earth,,,,,32,0.000,0.000,10.1080/17538947.2024.2344592,https://www.semanticscholar.org/paper/699a3ece5d2fcc639ab25bf38bc9bc888765637c,https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2344592?needAccess=true,semantic_scholar,,"ABSTRACT The multi-angle method in the pixel dichotomy model (PDM) is used to produce fine spatial resolution (FSR) products of fractional vegetation cover (FVC), which involves numerous iterative computations. This phenomenon causes a low computational efficiency for global FVC. Here, we establishe"
644,,Effective and Lightweight Representation Learning for Link Sign Prediction in Signed Bipartite Graphs,Gyeongmin Gu; Minseo Jeon; Hyun-Je Song; Jinhong Jung,2024,arXiv.org,,,,,0,0.000,0.000,10.48550/arXiv.2412.18720,https://www.semanticscholar.org/paper/1402ccd7e4958c5835caf36f8d81b9470c4a9485,,semantic_scholar,,"How can we effectively and efficiently learn node representations in signed bipartite graphs? A signed bipartite graph is a graph consisting of two nodes sets where nodes of different types are positively or negative connected, and it has been extensively used to model various real-world relationshi"
645,,A dual‐interactive fusion network for low‐dose CT image denoising,Jingyi Wang; Weitao Wang; Yang Liu; Xiao Dong; Chen Lin,2025,Medical Physics,,,,,0,0.000,0.000,10.1002/mp.70253,https://openalex.org/W7117457534,,openalex,,"Abstract Background Low‐dose computed tomography (LDCT) has been widely adopted in clinical imaging to reduce radiation exposure. However, the inherent quantum noise and streaking artifacts in LDCT markedly degrade image quality, thereby compromising diagnostic accuracy. Purpose While conventional m"
646,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions/Added The Geometric Origin of Mass: First-Principles Derivation of the Compton Relation from Cosmic Speed Field Dynamics/Announcement: A relationship has been discovered for measuring nuclear masses. The file is attached./Added A Universal Lepton-Mass-Dependent Nuclear Charge Radius Scaling Law: Extension to 45 Nuclei with Exact Mathematical Consistency and 5σ Predictions/Added The Scale-Invariant Law of Galactic Dynamics: A Complete Theoretical Derivation and Empirical Validation/Added Universal Linear Correction to Nuclear Masses: A 79.7% Improvement Over the Bethe-Weizsäcker Formula",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.18062854,https://openalex.org/W7117360194,https://doi.org/10.5281/zenodo.18062854,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
647,,Efficient Exoplanet Imaging Simulations of the Habitable Worlds Observatory,Jamila S. Taaki; Farzad Kamalabadi; Athol J. Kemball; Lía Corrales; Alfred O. Hero,2025,The Astronomical Journal,,,,,0,0.000,0.000,10.3847/1538-3881/ae22f1,https://openalex.org/W7117122635,https://doi.org/10.3847/1538-3881/ae22f1,openalex,,"Abstract Direct imaging simulations of starshades and other proposed mission concepts are needed to characterize planet detection performance and inform mission design trades. In order to assess the complementary role of a 60 m starshade for the Habitable Worlds Observatory (HWO), we develop the opt"
648,,Intelligent integration of AI and IoT big data using QDCN for scalable smart manufacturing,Junqing Sheng; Junqing Sheng,2025,Discover Artificial Intelligence,,,,,0,0.000,0.000,10.1007/s44163-025-00711-0,https://openalex.org/W7115942081,https://doi.org/10.1007/s44163-025-00711-0,openalex,,"Abstract The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is revolutionizing industries, particularly manufacturing, by enabling intelligent, data-driven decision-making. However, traditional AI models face limitations when applied to resource-constrained IoT environm"
649,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions/Added The Geometric Origin of Mass: First-Principles Derivation of the Compton Relation from Cosmic Speed Field Dynamics/Announcement: A relationship has been discovered for measuring nuclear masses. The file is attached./Added A Universal Lepton-Mass-Dependent Nuclear Charge Radius Scaling Law: Extension to 45 Nuclei with Exact Mathematical Consistency and 5σ Predictions/Added The Scale-Invariant Law of Galactic Dynamics: A Complete Theoretical Derivation and Empirical Validation",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17963913,https://openalex.org/W7115933012,https://doi.org/10.5281/zenodo.17963913,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
650,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions/Added The Geometric Origin of Mass: First-Principles Derivation of the Compton Relation from Cosmic Speed Field Dynamics/Announcement: A relationship has been discovered for measuring nuclear masses. The file is attached./Added A Universal Lepton-Mass-Dependent Nuclear Charge Radius Scaling Law: Extension to 45 Nuclei with Exact Mathematical Consistency and 5σ Predictions",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17884193,https://openalex.org/W7114892441,https://doi.org/10.5281/zenodo.17884193,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
651,,Bhosale's First Law — Empirical Verification Bundle v1.3 (Real Data Edition),shrikant bhosale,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17896919,https://openalex.org/W7114903045,https://doi.org/10.5281/zenodo.17896919,openalex,,"Bhosale’s First Law — Empirical Verification Bundle v1.3 (Real Data Edition) Version 1.3 represents a major milestone in the development and validation of Bhosale’s Inverse Scaling Law, transitioning the project from a simulation-driven conceptual framework into a fully empirical, reproducible scien"
652,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions/Added The Geometric Origin of Mass: First-Principles Derivation of the Compton Relation from Cosmic Speed Field Dynamics/Announcement: A relationship has been discovered for measuring nuclear masses. The file is attached.",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17840735,https://openalex.org/W7109537994,https://doi.org/10.5281/zenodo.17840735,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
653,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions/Added The Geometric Origin of Mass: First-Principles Derivation of the Compton Relation from Cosmic Speed Field Dynamics",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17840650,https://openalex.org/W7109587971,https://doi.org/10.5281/zenodo.17840650,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
654,,Pressure sampling design in water distribution systems using graph partitioning and entropy,Suocheng Wei; Chengyin Liu; Zhigang Liu; Shipeng Chu; Tingchao Yu,2025,AQUA - Water Infrastructure Ecosystems and Society,,,,,0,0.000,0.000,10.2166/aqua.2025.087,https://openalex.org/W4417336165,https://iwaponline.com/aqua/article-pdf/doi/10.2166/aqua.2025.087/1602046/jws2025087.pdf,openalex,,"ABSTRACT Hydraulic models of water distribution systems (WDSs) play a crucial role in system planning, design, and management. The nodal water demand, a key parameter in such models, must be accurately estimated based on pressure measurements within the network. An appropriate pressure sampling desi"
655,,Game-Theoretic Explainable AI for Ensemble-Boosting Models in Early Malware Prediction for Computer Systems,Shagufta Henna; Lakshya Gourav Moitra; Upaka Rathnayake,2025,International Journal of Computational Intelligence Systems,,,,,0,0.000,0.000,10.1007/s44196-025-01011-2,https://openalex.org/W4416791839,https://doi.org/10.1007/s44196-025-01011-2,openalex,,"Abstract Malware continues to pose a critical threat to computing systems, with modern techniques often bypassing traditional signature-based defenses. Ensemble-boosting classifiers, including GBC, XGBoost, AdaBoost, LightGBM, and CatBoost, have shown strong predictive performance for malware detect"
656,,Adaptive Bottleneck Architecture Search for Resource-Constrained Continual Learning,Weijun Liu; Haoming Chen; Liang Zhan; Jiaxin Wu; Zhou Shen,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-8201329/v1,https://openalex.org/W4416731387,https://www.researchsquare.com/article/rs-8201329/latest.pdf,openalex,,"<title>Abstract</title> In this paper, we propose an innovative framework for addressing the dual challenges of neural architecture selection and resource allocation in resource-constrained continual learning environments. We formulate the adaptive bottleneck architecture search (ABAS) as a mixed-in"
657,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena/Nuclear physics has been added Experimental Evidence of Lepton-Mass-Dependent Nuclear Charge Radius Scaling in Precision Lepton-Hadron Interactions",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17681402,https://openalex.org/W7106231955,https://doi.org/10.5281/zenodo.17681402,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
658,,Multi-scale dynamic spatio-temporal graph trend seasonality network for traffic flow forecasting,Qiang Ren; Baiying Yang,2025,Measurement Science and Technology,,,,,0,0.000,0.000,10.1088/1361-6501/ae20b1,https://openalex.org/W4416767108,,openalex,,"Abstract Traffic flow prediction is fundamental to traffic management and scheduling decisions in intelligent transportation systems. Traffic flow data exhibit complex spatiotemporal dynamics, multi-scale nonlinearities, and pronounced trend and seasonal patterns. Consequently, conventional statisti"
659,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.An update regarding comets has been added.FST Complete Anomaly Resolution: 3I/ATLAS and Interstellar Object Phenomena",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17641423,https://openalex.org/W7105984319,https://doi.org/10.5281/zenodo.17641423,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
660,,"χ²/dof = 0.189 Added protected inventions and patents Definitive ""Fundamental Speed Theory"" (FST) Update on the cosmic Black holes theory added,Also solve two of the millennium problems interstellar and galactic levels Speed Theory (FST) proposes a dynamical four-vector field \(V^\mu\) as a fundamental entity of spacetime. This theory offers a unified solution to dark matter (via a novel velocity-derived density \(\rho_V\)), baryon asymmetry (through early-universe CP violation), and gravitational lensing anomalies. FST successfully fits 175 SPARC galaxies (\(\chi^2/\text{dof}=0.189\)), satisfies solar-system tests via a screening mechanism, and predicts distinct signatures like an additional gravitational wave polarization mode. It challenges the \(\Lambda\)CDM paradigm by geometrizing motion itself.",RAHEB ALI MOHAMMED SALEH AOUDH,2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.000,10.5281/zenodo.17631239,https://openalex.org/W7105965505,https://doi.org/10.5281/zenodo.17631239,openalex,,"To all who carry a passion for science,To those who believe that knowledge belongs not to geography, but to the mind— my name /RAHEB ALI MOHAMMED SALEH AOUDH/From Yemen, in the Ibb Governorate, I am an independent researcher. I faced difficulties because I am from Yemen, and you know the situation. "
661,,Analysis of Generative Adversarial Network-based Models for Image Translation,Shelley Gupta,2025,Recent Advances in Computer Science and Communications,,,,,0,0.000,0.000,10.2174/0126662558385734251024105830,https://openalex.org/W4416224471,,openalex,,"Abstract: Generative Adversarial Networks (GANs) have significantly enhanced image-toimage translation, enabling high-quality transformations across various domains. However, existing models often lack interpretability, control over translation outcomes, and adaptability, leading to challenges in ac"
662,,Analytical benchmark problems and methodological framework for the assessment and comparison of multifidelity optimization methods,Laura Mainini; Andrea Serani; Hayriye Pehlivan Solak; Francesco Di Fiore; Markus P. Rumpfkeil,2025,Archives of Computational Methods in Engineering,,,,,0,0.000,0.000,10.1007/s11831-025-10392-8,https://openalex.org/W4416068500,https://link.springer.com/content/pdf/10.1007/s11831-025-10392-8.pdf,openalex,,"Abstract As engineering systems increase in complexity and performance demands intensify, Multidisciplinary Design Optimization (MDO) methodologies are becoming essential for integrating models from multiple disciplines to optimize complex multi-physics systems. Within this context, major challenges"
663,,Efficient Knowledge Graph Unlearning with Zeroth-order Information,Yang Xiao; Runchuan Ye; Bohan Liu; Xiaolong Ma; Bo Hui,2025,,,,,,0,0.000,0.000,10.1145/3746252.3761379,https://openalex.org/W4415014309,https://doi.org/10.1145/3746252.3761379,openalex,,"Due to regulations like the Right to be Forgotten, there is growing demand for removing training data and its influence from models. Since full retraining is costly, various machine unlearning methods have been proposed. In this paper, we firstly present an efficient knowledge graph (KG) unlearning "
664,,Development of hybrid optimization approach combined with AI-based techniques for prediction of electrical fields in overhead transmission lines,Takieddine Meriouma; Sid Ahmed Bessedik; Rabah Djekidel; Ragab A. El‐Sehiemy,2025,The Journal of Supercomputing,,,,,0,0.000,0.000,10.1007/s11227-025-08013-z,https://openalex.org/W4415959333,https://link.springer.com/content/pdf/10.1007/s11227-025-08013-z.pdf,openalex,,"Abstract Getting a precise estimate of electric fields around extra-high-voltage (EHV) transmission lines is essential for keeping the public safe, ensuring environmental compliance, and planning infrastructure effectively. Unfortunately, traditional numerical methods often struggle with accuracy an"
665,,Research on Corporate Financial Anomaly Detection and Early Warning System Based on <scp>SVM</scp> ‐ <scp>LightBGM</scp>,Yonggang Wang,2025,Security and Privacy,,,,,0,0.000,0.000,10.1002/spy2.70107,https://openalex.org/W4415780462,,openalex,,"ABSTRACT As enterprise operations become more complex and financial data volumes grow rapidly, traditional methods for detecting financial anomalies are increasingly inadequate for management needs. This study proposes a new model for financial anomaly detection and early warning. The model is based"
666,,Advancements in 3-D object detection: A comprehensive review,Wen-Jong Wu; Innocent Appiah; Rui Hu,2025,Journal of King Saud University - Computer and Information Sciences,,,,,0,0.000,0.000,10.1007/s44443-025-00213-0,https://openalex.org/W4415805331,https://doi.org/10.1007/s44443-025-00213-0,openalex,,"Abstract 3-D object detection has become essential for autonomous systems, yet the field remains fragmented due to diverse sensor modalities, fusion strategies, and architectural designs. This review aims to unify current approaches by proposing a taxonomy based on fusion granularity, early, mid, an"
667,,Brain Topology Disruption in Early‐Onset Dementia: Review of Current Findings and the Need for Network Resilience Focused Models,Hema Nawani; Soorya Sunil; Ranjith Jaganathan; Veeky Baths,2025,Brain and Behavior,,,,,0,0.000,0.000,10.1002/brb3.70903,https://openalex.org/W4416343706,https://doi.org/10.1002/brb3.70903,openalex,,"ABSTRACT Introduction Early‐Onset Dementia (EOD), including Frontotemporal Dementia (FTD), behavioral variant FTD (bvFTD), and Early‐Onset Alzheimer’s Disease (EOAD), presents significant diagnostic and therapeutic challenges due to heterogeneous clinical features and rapid progression. EOD involves"
668,,Enhancing Retinal Disease Detection With the Swin Transformer: A Comprehensive Comparative Analysis,Ahmet Saygılı; Ömer Mutlu Atıcı,2025,Concurrency and Computation Practice and Experience,,,,,0,0.000,0.000,10.1002/cpe.70366,https://openalex.org/W4415673361,,openalex,,"ABSTRACT Retinal fundus image classification is paramount for the early detection and management of blinding eye diseases, such as diabetic retinopathy, glaucoma, and cataracts. This study systematically evaluates and compares various deep learning models for retinal disease classification, includin"
669,,A Selection Framework for Distilled AI Models in IoT-based Edge Applications,Hamad Almansour,2025,,,,,,0,0.000,0.000,10.21203/rs.3.rs-7557310/v1,https://openalex.org/W4415625660,https://www.researchsquare.com/article/rs-7557310/latest.pdf,openalex,,<title>Abstract</title> The rapid expansion of artificial intelligence (AI) in edge and Internet of Things (IoT) applications calls for the efficient deployment of lightweight AI models suited to resource-constrained edge applications. Knowledge distillation has become a key technique for compressin
670,,Haptic Shared Control of a Pair of Microrobots for Telemanipulation using Constrained Optimization,Leon Raphalen; Marco Ferro; Sarthak Misra; Paolo Robuffo Giordano; Claudio Pacchierotti,2025,,,,,,0,0.000,0.000,10.1109/iros60139.2025.11247670,https://openalex.org/W4415194463,https://hal.science/hal-05157735v1/file/HapticSharedControlForTelemanipulation.pdf,openalex,,International audience
671,,Dual-Stream Convolutional Networks for Scalable and Precise Water Body Mapping from Multispectral Earth Observation Imagery,Abdelali Benali; Hayet Kharbouch; Mohamed Della Krachai; Juginder Pal Singh; Riyadh Bouddou,2025,International Journal of Computational Intelligence Systems,,,,,0,0.000,0.000,10.1007/s44196-025-00985-3,https://openalex.org/W4415039969,https://link.springer.com/content/pdf/10.1007/s44196-025-00985-3.pdf,openalex,,"Abstract Reliable segmentation of surface water is crucial for monitoring hydrological dynamics, mitigating disaster impacts, and supporting climate-resilient infrastructure development. However, traditional approaches based on spectral indices—such as the Normalized Difference Water Index (NDWI)—of"
672,,Integrating machine learning and encryption for effective data management in blood bank supply chains,K. Shankar; V. Santhi,2025,Journal of Cloud Computing Advances Systems and Applications,,,,,0,0.000,0.000,10.1186/s13677-025-00779-0,https://openalex.org/W4414994809,https://journalofcloudcomputing.springeropen.com/counter/pdf/10.1186/s13677-025-00779-0,openalex,,"Abstract The security and efficient management of healthcare data—especially in blood bank supply chains are of paramount importance due to the sensitive, diverse, and time-critical nature of the information involved. Existing approaches frequently fall short in balancing data protection, computatio"
673,,A Survey on Model Compression for Large Language Models,Xunyu Zhu; Jian Li; Yong Liu; Can Ma; Weiping Wang,2023,Transactions of the Association for Computational Linguistics,,,,,347,0.000,0.000,10.1162/tacl_a_00704,https://www.semanticscholar.org/paper/338d8f3b199abcebc85f34016b0162ab3a9d5310,,semantic_scholar,,"Abstract Large Language Models (LLMs) have transformed natural language processing tasks successfully. Yet, their large size and high computational needs pose challenges for practical use, especially in resource-limited settings. Model compression has emerged as a key research area to address these "
674,,"A survey on augmenting knowledge graphs (KGs) with large language models (LLMs): models, evaluation metrics, benchmarks, and challenges",Nourhan Ibrahim; Samar AboulEla; A. Ibrahim; R. Kashef,2024,Discover Artificial Intelligence,,,,,60,0.000,0.000,10.1007/s44163-024-00175-8,https://www.semanticscholar.org/paper/3a5177089aa62aadd2abbfb859625c92f794737c,https://doi.org/10.1007/s44163-024-00175-8,semantic_scholar,,"Integrating Large Language Models (LLMs) with Knowledge Graphs (KGs) enhances the interpretability and performance of AI systems. This research comprehensively analyzes this integration, classifying approaches into three fundamental paradigms: KG-augmented LLMs, LLM-augmented KGs, and synergized fra"
675,,ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration,Chaojun Ni; Guosheng Zhao; Xiaofeng Wang; Zheng Zhu; Wenkang Qin,2024,Computer Vision and Pattern Recognition,,,,,50,0.000,0.000,10.1109/CVPR52734.2025.00153,https://www.semanticscholar.org/paper/af45e21a4b036fb3e2d30ba3b10978233daeda0e,,semantic_scholar,,"Closed-loop simulation is crucial for end-to-end autonomous driving. Existing sensor simulation methods (e.g., NeRF and 3DGS) reconstruct driving scenes based on conditions that closely mirror training data distributions. However, these methods struggle with rendering novel trajectory, such as lane "
676,,Accelerating Model-Based Reinforcement Learning with State-Space World Models,Maria Krinner; Elie Aljalbout; Angel Romero; Davide Scaramuzza,2025,arXiv.org,,,,,7,0.000,0.000,10.48550/arXiv.2502.20168,https://www.semanticscholar.org/paper/6d8f165d6fdcf175c54870225703a03a4fe417d4,,semantic_scholar,,"Reinforcement learning (RL) is a powerful approach for robot learning. However, model-free RL (MFRL) requires a large number of environment interactions to learn successful control policies. This is due to the noisy RL training updates and the complexity of robotic systems, which typically involve h"
677,,Long-Context State-Space Video World Models,Ryan Po; Yotam Nitzan; Richard Zhang; Berlin Chen; Tri Dao,2025,arXiv.org,,,,,24,0.000,0.000,10.48550/arXiv.2505.20171,https://www.semanticscholar.org/paper/51393dfbfd50a47030023c1ea1ef9f8e4a18941d,,semantic_scholar,,"Video diffusion models have recently shown promise for world modeling through autoregressive frame prediction conditioned on actions. However, they struggle to maintain long-term memory due to the high computational cost associated with processing extended sequences in attention layers. To overcome "
678,,Locality Sensitive Sparse Encoding for Learning World Models Online,Zi-Yan Liu; Chao Du; Wee Sun Lee; Min Lin,2024,International Conference on Learning Representations,,,,,18,0.000,0.000,10.48550/arXiv.2401.13034,https://www.semanticscholar.org/paper/534363ddcdddb15decdaf9f8e6c277545518f775,,semantic_scholar,,"Acquiring an accurate world model online for model-based reinforcement learning (MBRL) is challenging due to data nonstationarity, which typically causes catastrophic forgetting for neural networks (NNs). From the online learning perspective, a Follow-The-Leader (FTL) world model is desirable, which"
679,,Efficiency metrics for auditory neuromorphic spike encoding techniques using information theory,Ahmad El Ferdaoussi; J. Rouat; É. Plourde,2023,Neuromorph. Comput. Eng.,,,,,5,0.000,0.000,10.1088/2634-4386/acd952,https://www.semanticscholar.org/paper/cb0eeace5aa9efd8db399242b94287455b9986e0,https://iopscience.iop.org/article/10.1088/2634-4386/acd952/pdf,semantic_scholar,,"Spike encoding of sound consists in converting a sound waveform into spikes. It is of interest in many domains, including the development of audio-based spiking neural network applications, where it is the first and a crucial stage of processing. Many spike encoding techniques exist, but there is no"
680,,Mercury: A Code Efficiency Benchmark for Code Large Language Models,Mingzhe Du; A. Luu; Bin Ji; Qian Liu; See-Kiong Ng,2024,Neural Information Processing Systems,,,,,28,0.000,0.000,10.52202/079017-0529,https://www.semanticscholar.org/paper/0c8fed8fd71b7a5c1dd0b06bd53ce73f24a5d13e,,semantic_scholar,,"Amidst the recent strides in evaluating Large Language Models for Code (Code LLMs), existing benchmarks have mainly focused on the functional correctness of generated code, neglecting the importance of their computational efficiency. To fill the gap, we present Mercury, the first code efficiency ben"
681,,Mastering Atari with Discrete World Models,Danijar Hafner; T. Lillicrap; Mohammad Norouzi; Jimmy Ba,2020,International Conference on Learning Representations,,,,,1040,0.000,0.000,,https://www.semanticscholar.org/paper/b44bb1762640ed72091fd5f5fdc20719a6dc24af,,semantic_scholar,,Intelligent agents need to generalize from past experience to achieve goals in complex environments. World models facilitate such generalization and allow learning behaviors from imagined outcomes to increase sample-efficiency. While learning world models from image inputs has recently become feasib
682,,Exploring the limits of hierarchical world models in reinforcement learning,Robin Schiewer; Anand Subramoney; Laurenz Wiskott,2024,Scientific Reports,,,,,7,0.000,0.000,10.1038/s41598-024-76719-w,https://www.semanticscholar.org/paper/23321c6006dab5030019e72af0cefc896ece1dcf,https://doi.org/10.1038/s41598-024-76719-w,semantic_scholar,,"Hierarchical model-based reinforcement learning (HMBRL) aims to combine the sample efficiency of model-based reinforcement learning with the abstraction capability of hierarchical reinforcement learning. While HMBRL has great potential, the structural and conceptual complexities of current approache"
683,,DITTO: Offline Imitation Learning with World Models,Branton DeMoss; Paul Duckworth; Nick Hawes; I. Posner,2023,arXiv.org,,,,,21,0.000,0.000,10.48550/arXiv.2302.03086,https://www.semanticscholar.org/paper/51742dadd56e4703a2dce60add6c3181f2e7644d,http://arxiv.org/pdf/2302.03086,semantic_scholar,,"For imitation learning algorithms to scale to real-world challenges, they must handle high-dimensional observations, offline learning, and policy-induced covariate-shift. We propose DITTO, an offline imitation learning algorithm which addresses all three of these problems. DITTO optimizes a novel di"
684,,Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models,Deepak Narayanan; Keshav Santhanam; Peter Henderson; Rishi Bommasani; Tony Lee,2023,Neural Information Processing Systems,,,,,13,0.000,0.000,,https://www.semanticscholar.org/paper/eec73c865db0f3e882ccb5951879de0eff423266,,semantic_scholar,,
685,,Assessing Adaptive World Models in Machines with Novel Games,Lance Ying; Katherine M. Collins; Prafull Sharma; C'edric Colas; Kaiya Ivy Zhao,2025,arXiv.org,,,,,10,0.000,0.000,10.48550/arXiv.2507.12821,https://www.semanticscholar.org/paper/f7042efe993787005c17fbb2a2d014730aff2b7d,,semantic_scholar,,"Human intelligence exhibits a remarkable capacity for rapid adaptation and effective problem-solving in novel and unfamiliar contexts. We argue that this profound adaptability is fundamentally linked to the efficient construction and refinement of internal representations of the environment, commonl"
686,,THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models,Zhiyuan Li; Yi Chang; Yuan Wu,2025,arXiv.org,,,,,6,0.000,0.000,10.48550/arXiv.2505.22113,https://www.semanticscholar.org/paper/e1961dfa28c2b6d490afec9190954ae57b481886,,semantic_scholar,,"Large reasoning models (LRMs) have achieved impressive performance in complex tasks, often outperforming conventional large language models (LLMs). However, the prevalent issue of overthinking severely limits their computational efficiency. Overthinking occurs when models generate excessive and redu"
687,,Hybrid Swarm Intelligence-Based Neural Framework for Optimizing Real-Time Computational Models in Engineering Systems,Bhuvaneshwarri; M. Maheswari; C. Kalaivanan; P. Deepthi; Tatiraju V. Rajani Kanth,2025,International Journal of Computational and Experimental Science and Engineering,,,,,6,0.000,0.000,10.22399/ijcesen.1001,https://www.semanticscholar.org/paper/4c5016b7cb4686160d97acd989b49d60d9d842fd,https://doi.org/10.22399/ijcesen.1001,semantic_scholar,,"In modern engineering systems, real-time computational models are essential for optimizing performance, enhancing decision-making, and reducing latency in complex environments. This research presents a Hybrid Swarm Intelligence-Based Neural Framework (HSIN-F) to improve the efficiency, accuracy, and"
688,,Self-Attention Over Tree for Relation Extraction With Data-Efficiency and Computational Efficiency,Shengfei Lyu; Xiren Zhou; Xingyu Wu; Qiuju Chen; Huanhuan Chen,2024,IEEE Transactions on Emerging Topics in Computational Intelligence,,,,,6,0.000,0.000,10.1109/TETCI.2023.3286268,https://www.semanticscholar.org/paper/640c52da10ac2dfcc333b2df2165c03e480fe860,,semantic_scholar,,"Dependency trees parsed from natural language sentences have been proven to be beneficial for the relation extraction task by deep neural networks. However, effectively and efficiently utilizing the structural information of dependency trees remains a challenging research problem for neural networks"
689,,xCOMET-lite: Bridging the Gap Between Efficiency and Quality in Learned MT Evaluation Metrics,Daniil Larionov; Mikhail Seleznyov; Vasiliy Viskov; Alexander Panchenko; Steffen Eger,2024,Conference on Empirical Methods in Natural Language Processing,,,,,9,0.000,0.000,10.48550/arXiv.2406.14553,https://www.semanticscholar.org/paper/a1917a9f429a65522e872a523fb9e0d2e8cf08d1,,semantic_scholar,,"State-of-the-art trainable machine translation evaluation metrics like xCOMET achieve high correlation with human judgment but rely on large encoders (up to 10.7B parameters), making them computationally expensive and inaccessible to researchers with limited resources. To address this issue, we inve"
690,,Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models,Guangji Bai; Zheng Chai; Chen Ling; Shiyu Wang; Jiaying Lu,2024,arXiv.org,,,,,75,0.000,0.000,10.48550/arXiv.2401.00625,https://www.semanticscholar.org/paper/001cca7910f507f7f75b8402b826c2dc07afef00,,semantic_scholar,,"The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in the high consumption of computational, memory, energy, and fi"
691,,A Stable Wavelet Computational Method for the Study of Generalized Burger–Fisher and Burgers–Huxley Models,Aslam Khan; Abdul Ghafoor; Kamal Shah; T. Abdeljawad; Manar A. Alqudah,2025,Journal of Computational and Theoretical Transport,,,,,0,0.000,0.000,10.1080/23324309.2025.2580614,https://www.semanticscholar.org/paper/ab3b5e362be84c4ba0eb4f8885d3c2d21f0a0a69,,semantic_scholar,,"Abstract This work proposes, a hybrid numerical scheme to study the generalized Burger–Fisher equation (gBFE) and generalized Burgers-Huxley equation (gBHE). This strategy comprises Haar wavelet and Runge-Kutta (RK-4) routine solver. We use the collocation approach to approximate the unknown solutio"
692,,Estimation of the Unidirectional Traffic Flow Velocity Limit with High Computational Efficiency,Ivan A. Kuteynikov,2025,COMPUTATIONAL MATHEMATICS AND INFORMATION TECHNOLOGIES,,,,,0,0.000,0.000,10.23947/2587-8999-2025-9-1-39-51,https://www.semanticscholar.org/paper/153988bc9eebcf4730eb2495545b510472c6a7bb,https://doi.org/10.23947/2587-8999-2025-9-1-39-51,semantic_scholar,,"Introduction. In the modern development of intelligent transportation systems (ITS), an urgent task is the accurate estimation of the velocity limit of traffic flow on a highway. Despite existing solutions to this problem based on statistical mechanics methods and stochastic models, gaps remain in a"
693,,"Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling",B. Moya; Alberto Badías; D. González; Francisco Chinesta; Elías Cueto,2023,Archives of Computational Methods in Engineering,,,,,9,0.000,0.000,10.1007/s11831-023-10033-y,https://www.semanticscholar.org/paper/474486cc80293ae19cc4f841e87a04caa34b9ca6,,semantic_scholar,,
694,,"Optimizing Large Language Models in Distributed Environments: A Holistic Approach to Efficiency, Ethics, and Governance",Mubarak Ahmad; Abdulkadhem A. Abdulkadhem; Umar Islam; H. Alwageed; Hanif Ullah,2025,International Journal of Computational Intelligence Systems,,,,,1,0.000,0.000,10.1007/s44196-025-00992-4,https://www.semanticscholar.org/paper/cdc57389b9d5408d14e4a29032b458c32e65651c,,semantic_scholar,,
695,,VLMInferSlow: Evaluating the Efficiency Robustness of Large Vision-Language Models as a Service,Xiasi Wang; Tianliang Yao; Simin Chen; Runqi Wang; Lei Ye,2025,Annual Meeting of the Association for Computational Linguistics,,,,,1,0.000,0.000,10.48550/arXiv.2506.15755,https://www.semanticscholar.org/paper/7d9a66bc8ea9ca90bcffaab29624e852e98e7ca1,,semantic_scholar,,"Vision-Language Models (VLMs) have demonstrated great potential in real-world applications. While existing research primarily focuses on improving their accuracy, the efficiency remains underexplored. Given the real-time demands of many applications and the high inference overhead of VLMs, efficienc"
696,,Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts,X. Shi; Shiyu Wang; Yuqi Nie; Dianqi Li; Zhou Ye,2024,International Conference on Learning Representations,,,,,159,0.000,0.000,10.48550/arXiv.2409.16040,https://www.semanticscholar.org/paper/2cb3044ef42c7ee022a988864028b80ce977072c,,semantic_scholar,,"Deep learning for time series forecasting has seen significant advancements over the past decades. However, despite the success of large-scale pre-training in language and vision domains, pre-trained time series models remain limited in scale and operate at a high cost, hindering the development of "
697,,Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey,Xiaoou Liu; Tiejin Chen; Longchao Da; Chacha Chen; Zhen Lin,2025,Knowledge Discovery and Data Mining,,,,,37,0.000,0.000,10.1145/3711896.3736569,https://www.semanticscholar.org/paper/422b00c330a16a00ef182abfd1d66e12369db9e8,,semantic_scholar,,"Uncertainty quantification (UQ) enhances the reliability of Large Language Models (LLMs) by estimating confidence in outputs, enabling risk mitigation and selective prediction. However, traditional UQ methods struggle with LLMs due to computational constraints and decoding inconsistencies. Moreover,"
698,,A Comprehensive Study of Feature Selection Techniques in Machine Learning Models,Xueyi Cheng,2024,"Insights in Computer, Signals and Systems",,,,,43,0.000,0.000,10.70088/xpf2b276,https://www.semanticscholar.org/paper/1b4287acba75335c536767a8cdeaaa101ad7b51c,https://soapubs.com/index.php/ICSS/article/download/217/232,semantic_scholar,,"This paper explores the importance and applications of feature selection in machine learning models, with a focus on three main feature selection methods: filter methods, wrapper methods, and embedded methods. By comparing their advantages and limitations, the paper highlights how feature selection "
699,,NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image Caption Generation Models,Simin Chen; Zihe Song; Mirazul Haque; Cong Liu; Wei Yang,2022,Computer Vision and Pattern Recognition,,,,,50,0.000,0.000,10.1109/CVPR52688.2022.01493,https://www.semanticscholar.org/paper/7afc3335a0e6980147ca7b56a7698b380fbc1b7d,https://arxiv.org/pdf/2203.15859,semantic_scholar,,"Neural image caption generation (NICG) models have received massive attention from the research community due to their excellent performance in visual understanding. Existing work focuses on improving NICG model ac-curacy while efficiency is less explored. However, many real-world applications requi"
700,,AudioLDM: Text-to-Audio Generation with Latent Diffusion Models,Haohe Liu; Zehua Chen; Yiitan Yuan; Xinhao Mei; Xubo Liu,2023,International Conference on Machine Learning,,,,,657,0.000,0.000,10.48550/arXiv.2301.12503,https://www.semanticscholar.org/paper/fa0f3d8aa20e8987dbc7a516d5399cfa3dc97b1b,https://arxiv.org/pdf/2301.12503,semantic_scholar,,"Text-to-audio (TTA) system has recently gained attention for its ability to synthesize general audio based on text descriptions. However, previous studies in TTA have limited generation quality with high computational costs. In this study, we propose AudioLDM, a TTA system that is built on a latent "
701,,A point field driven approach to process metrics based on laser powder bed fusion additive manufacturing models and in situ process monitoring,Samuel J. A. Hocker; B. Richter; Peter W. Spaeth; Andrew R. Kitahara; J. Zalameda,2023,Journal of Materials Research,,,,,12,0.000,0.000,10.1557/s43578-023-00953-7,https://www.semanticscholar.org/paper/174310873576c9959a928ca569950755ba9634f9,https://link.springer.com/content/pdf/10.1557/s43578-023-00953-7.pdf,semantic_scholar,,The widespread adoption of additive manufacturing (AM) in different industries has accelerated the need for quality control of these AM parts. Some of the complex and labor-intensive challenges associated with qualification and certification of AM parts are addressed by modeling and monitoring proce
702,,Comparing pre-trained models for efficient leaf disease detection: a study on custom CNN,Touhidul Seyam Alam; Chandni Barua Jowthi; Abhijit Pathak,2024,Journal of Electrical Systems and Information Technology,,,,,35,0.000,0.000,10.1186/s43067-024-00137-1,https://www.semanticscholar.org/paper/d7d080a03b642ae85c584c050b47180d98f90911,https://jesit.springeropen.com/counter/pdf/10.1186/s43067-024-00137-1,semantic_scholar,,"Leaf disease detection is a crucial task in modern agriculture, aiding in early diagnosis and prevention of crop infections. In this research paper, authors present a comprehensive study comparing nine widely used pre-trained models, namely DenseNet201, EfficientNetB3, EfficientNetB4, InceptionResNe"
703,,"Large language models for software vulnerability detection: a guide for researchers on models, methods, techniques, datasets, and metrics",Seyed Mohammad Taghavi Far; Farid Feyzi,2025,International Journal of Information Security,,,,,9,0.000,0.000,10.1007/s10207-025-00992-7,https://www.semanticscholar.org/paper/32ec42ce96c2ea9fcba8461e309e2c2a0782cf29,,semantic_scholar,,
704,,LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting,Haoxin Liu; Zhiyuan Zhao; Jindong Wang; Harshavardhan Kamarthi; B. A. Prakash,2024,Annual Meeting of the Association for Computational Linguistics,,,,,57,0.000,0.000,10.48550/arXiv.2402.16132,https://www.semanticscholar.org/paper/bbf272d92b76cc5f1e6f793dcfeb5edd4abed7ef,,semantic_scholar,,"Time-series forecasting (TSF) finds broad applications in real-world scenarios. Prompting off-the-shelf Large Language Models (LLMs) demonstrates strong zero-shot TSF capabilities while preserving computational efficiency. However, existing prompting methods oversimplify TSF as language next-token p"
705,,VisionZip: Longer is Better but Not Necessary in Vision Language Models,Senqiao Yang; Yukang Chen; Zhuotao Tian; Chengyao Wang; Jingyao Li,2024,Computer Vision and Pattern Recognition,,,,,102,0.000,0.000,10.1109/CVPR52734.2025.01843,https://www.semanticscholar.org/paper/ab36ffad0a5364b17d3a73ea3258c5ae4068c341,,semantic_scholar,,"Recent advancements in vision-language models have enhanced performance by increasing the length of visual tokens, making them much longer than text tokens and significantly raising computational costs. However, we observe that the visual tokens generated by popular vision encoders, such as CLIP and"
706,,Verifiable evaluations of machine learning models using zkSNARKs,Tobin South; Alexander Camuto; Shrey Jain; Shayla Nguyen; Robert Mahari,2024,arXiv.org,,,,,18,0.000,0.000,10.48550/arXiv.2402.02675,https://www.semanticscholar.org/paper/53c45ebc39118801a87838152389346319a0eef7,,semantic_scholar,,"In a world of increasing closed-source commercial machine learning models, model evaluations from developers must be taken at face value. These benchmark results-whether over task accuracy, bias evaluations, or safety checks-are traditionally impossible to verify by a model end-user without the cost"
707,,Aligning Human and Computational Coherence Evaluations,Jia Peng Lim; Hady W. Lauw,2024,Computational Linguistics,,,,,10,0.000,0.000,10.1162/coli_a_00518,https://www.semanticscholar.org/paper/1b0f8836ea604a0e2298ea00fe141989e4422fa7,https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00518/2368812/coli_a_00518.pdf,semantic_scholar,,Abstract Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous work presents a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mining topic representations at a large scale while seeking
708,,Hybrid Computational Intelligence Models for Robust Pattern Recognition and Data Analysis,J. Jeyasudha; K. Deiwakumari; C. A. Arun; R. Pushpavalli; P. P. Selvam,2024,International Journal of Computational and Experimental Science and Engineering,,,,,15,0.000,0.000,10.22399/ijcesen.624,https://www.semanticscholar.org/paper/cf67f74811e58233ad98d84ac7b31703891c37a6,https://doi.org/10.22399/ijcesen.624,semantic_scholar,,"In the era of big data, robust pattern recognition and accurate data analysis have become critical in various fields, including healthcare, finance, and industrial automation. This study presents a novel hybrid computational intelligence model that integrates deep learning techniques and evolutionar"
709,,Explainable machine learning models for estimating daily dissolved oxygen concentration of the Tualatin River,Shuguang Li; Sultan Noman Qasem; Shahab S. Band; Rasoul Ameri; Hao-Ting Pai,2024,Engineering Applications of Computational Fluid Mechanics,,,,,8,0.000,0.000,10.1080/19942060.2024.2304094,https://www.semanticscholar.org/paper/bf2a7fce57f745c4a602d9ce9358843f376ac839,https://www.tandfonline.com/doi/pdf/10.1080/19942060.2024.2304094?needAccess=true,semantic_scholar,,"ABSTRACT Monitoring the quality of river water is of fundamental importance and needs to be taken into consideration when it comes to the research into the hydrological field. In this context, the concentration of the dissolved oxygen (DO) is one of the most significant indicators of the quality of "
710,,A Survey of Small Language Models,C. Nguyen; Xuan Shen; Ryan Aponte; Yu Xia; Samyadeep Basu,2024,arXiv.org,,,,,32,0.000,0.000,10.48550/arXiv.2410.20011,https://www.semanticscholar.org/paper/bee5db90312bc27ce5a444ffe28c8d167fd39a7d,,semantic_scholar,,"Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, making them ideal for various settings including on-device, mobile, edge devices, among many others. In this article, we pre"
711,,"Predicting Cervical Cancer with Deep Learning: Comparative Analysis of VGGNet, GoogleNet, and DenseNet121 Models",Arshleen Kaur; Rishabh Sharma; Richa Gupta; Ashish Garg,2024,2024 2nd World Conference on Communication & Computing (WCONF),,,,,2,0.000,0.000,10.1109/WCONF61366.2024.10691964,https://www.semanticscholar.org/paper/e8be460ce367c467310c71ae744f83a7af90daee,,semantic_scholar,,"The proposed study compares the efficacy, degree of accuracy, and computational efficiency of three deep learning algorithms, namely, VGGNet, GoogleNet, and DenseNet121, in terms of their capacity to determine cervical cancer from smear images and thus further the role of artificial intelligence in "
712,,"Sparse Topic Modeling: Computational Efficiency, Near-Optimal Algorithms, and Statistical Inference",Ruijia Wu; Linjun Zhang; T. Tony Cai,2021,Journal of the American Statistical Association,,,,,13,0.000,0.000,10.1080/01621459.2021.2018329,https://www.semanticscholar.org/paper/7110762f663a089d119d7994d702c989cadfc9e2,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530787,semantic_scholar,,Abstract Sparse topic modeling under the probabilistic latent semantic indexing (pLSI) model is studied. Novel and computationally fast algorithms for estimation and inference of both the word-topic matrix and the topic-document matrix are proposed and their theoretical properties are investigated. 
713,,D2LLM: Decomposed and Distilled Large Language Models for Semantic Search,Zihan Liao; Hang Yu; Jianguo Li; Jun Wang; Wei Zhang,2024,Annual Meeting of the Association for Computational Linguistics,,,,,14,0.000,0.000,10.48550/arXiv.2406.17262,https://www.semanticscholar.org/paper/a68e474194a9ae04c1f80cb2a0de6276cbcdd636,,semantic_scholar,,"The key challenge in semantic search is to create models that are both accurate and efficient in pinpointing relevant sentences for queries. While BERT-style bi-encoders excel in efficiency with pre-computed embeddings, they often miss subtle nuances in search tasks. Conversely, GPT-style LLMs with "
714,,Efficient Vision-Language Models by Summarizing Visual Tokens into Compact Registers,Yuxin Wen; Qingqing Cao; Qichen Fu; Sachin Mehta; Mahyar Najibi,2024,arXiv.org,,,,,16,0.000,0.000,10.48550/arXiv.2410.14072,https://www.semanticscholar.org/paper/b371d90d4b0bbdde8f322c360dafc243cc1a47e4,,semantic_scholar,,"Recent advancements in vision-language models (VLMs) have expanded their potential for real-world applications, enabling these models to perform complex reasoning on images. In the widely used fully autoregressive transformer-based models like LLaVA, projected visual tokens are prepended to textual "
715,,SConU: Selective Conformal Uncertainty in Large Language Models,Zhiyuan Wang; Qingni Wang; Yue Zhang; Tianlong Chen; Xiaofeng Zhu,2025,Annual Meeting of the Association for Computational Linguistics,,,,,16,0.000,0.000,10.48550/arXiv.2504.14154,https://www.semanticscholar.org/paper/9372a46118666465db855b0bbe2ff730c4edfd41,,semantic_scholar,,"As large language models are increasingly utilized in real-world applications, guarantees of task-specific metrics are essential for their reliable deployment. Previous studies have introduced various criteria of conformal uncertainty grounded in split conformal prediction, which offer user-specifie"
716,,Artificial Intelligence in Mammography: A Study of Diagnostic Accuracy and Efficiency,Luaay Alswilem; Nurettin Paçal,2025,Computational Systems and Artificial Intelligence,,,,,6,0.000,0.000,10.69882/adba.csai.2025075,https://www.semanticscholar.org/paper/d7626da9434c1dbc9011faf16ce430a3c5e4a4c5,,semantic_scholar,,"Breast cancer continues to be a considerable global health problem, highlighting the need for early and accurate diagnosis to improve patient outcomes. Although mammography is widely considered the gold standard for screening, its interpretation is not straightforward and varies among readers. Our s"
717,,Advancing AI Interpretability in Medical Imaging: A Comparative Analysis of Pixel-Level Interpretability and Grad-CAM Models,Mohammad Ennab; Hamid Mcheick,2025,Machine Learning and Knowledge Extraction,,,,,38,0.000,0.000,10.3390/make7010012,https://www.semanticscholar.org/paper/1ecee1adcdc65415b8c44de989367790ed0df0ed,https://doi.org/10.3390/make7010012,semantic_scholar,,"This study introduces the Pixel-Level Interpretability (PLI) model, a novel framework designed to address critical limitations in medical imaging diagnostics by enhancing model transparency and diagnostic accuracy. The primary objective is to evaluate PLI’s performance against Gradient-Weighted Clas"
718,,Application of Stable Diffusion and LoRA Models in AI Drawing,Shunkai Gong,2024,Applied and Computational Engineering,,,,,0,0.000,0.000,10.54254/2755-2721/97/20241294,https://www.semanticscholar.org/paper/305f6c0cfdff5f6f668c96d9ddee94a4ed9b4cae,https://www.ewadirect.com/proceedings/ace/article/view/17568/pdf,semantic_scholar,,"Abstract. This paper explores the application of Stable Diffusion model and LoRA (Low-Rank Adaptation) model in AI-generated artwork. The authors introduce the foundational principles of Stable Diffusion model and LoRA, as well as their application in high-quality image generation. Using three popul"
719,,Toward Robust RALMs: Revealing the Impact of Imperfect Retrieval on Retrieval-Augmented Language Models,Seong-Il Park; Jay-Yoon Lee,2024,Transactions of the Association for Computational Linguistics,,,,,4,0.000,0.000,10.1162/tacl_a_00724,https://www.semanticscholar.org/paper/a6f3b65fba3ceaf80f2965e0358e3367bc6f185d,,semantic_scholar,,"Abstract Retrieval Augmented Language Models (RALMs) have gained significant attention for their ability to generate accurate answers and improve efficiency. However, RALMs are inherently vulnerable to imperfect information due to their reliance on the imperfect retriever or knowledge source. We ide"
720,,Evolution and advancements in deep learning models for Natural Language Processing,Yingxuan Chai; Liangning Jin; Shujie Feng; Zhuo Xin,2024,Applied and Computational Engineering,,,,,4,0.000,0.000,10.54254/2755-2721/77/20240674,https://www.semanticscholar.org/paper/a3aff256d671deccd5917af160a8624650e26adb,,semantic_scholar,,"This paper provides a comprehensive review of the evolution and advancements in deep learning models for Natural Language Processing (NLP). It explores the transition from statistical models to neural networks, highlighting the paradigm shift towards data-driven methodologies and the implications fo"
721,,Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models,Xinxin Liu; Aaron Thomas; Chengguo Zhang; Jianyi Cheng; Yiren Zhao,2024,Annual Meeting of the Association for Computational Linguistics,,,,,3,0.000,0.000,10.48550/arXiv.2412.13488,https://www.semanticscholar.org/paper/ac178652a099e2c0efc95696626d70661661caeb,,semantic_scholar,,"Parameter-Efficient Fine-Tuning (PEFT) has gained prominence through low-rank adaptation methods like LoRA. In this paper, we focus on sparsity-based PEFT (SPEFT), which introduces trainable sparse adaptations to the weight matrices in the model, offering greater flexibility in selecting fine-tuned "
722,,Computational 2D and 3D Medical Image Data Compression Models,S. Boopathiraja; V. Punitha; P. Kalavathi; V. B. Surya Prasath,2021,Archives of Computational Methods in Engineering,,,,,23,0.000,0.000,10.1007/s11831-021-09602-w,https://www.semanticscholar.org/paper/f22ed9488a8f7929d792840b8c892e88bcbb7436,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942405,semantic_scholar,,
723,,Data-Driven Spectral Analysis Through Pseudo-Resolvent Koopman Operator in Dynamical Systems,Yuanchao Xu; Itsushi Sakata; Isao Ishikawa,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24953v1,https://arxiv.org/pdf/2512.24953v1,arxiv,,"We present a data-driven method for spectral analysis of the Koopman operator based on direct construction of the pseudo-resolvent from time-series data. Finite-dimensional approximation of the Koopman operator, such as those obtained from Extended Dynamic Mode Decomposition, are known to suffer fro"
724,,Multi-particle quantum systems within the Worldline Monte Carlo formalism,Ivan Ahumada; Max Badcott; James P. Edwards; Craig McNeile; Filippo Ricchetti,2025,arXiv,,,,,0,0.000,0.000,,http://arxiv.org/abs/2512.24942v1,https://arxiv.org/pdf/2512.24942v1,arxiv,,We extend the Worldline Monte Carlo approach to computationally simulating the Feynman path integral of non-relativistic multi-particle quantum-mechanical systems. We show how to generate an arbitrary number of worldlines distributed according to the (free) kinetic part of the multi-particle quantum
725,,Comparison of Distributed and Parallel Machine Learning: Efficiency and Effectiveness in Large-Scale Data Processing,Chengszu Peng,2024,Applied and Computational Engineering,,,,,0,0.000,0.000,10.54254/2755-2721/96/20241279,https://www.semanticscholar.org/paper/15fae17b3dd7776aa9f0df228dbc6de501a8d46d,https://www.ewadirect.com/proceedings/ace/article/view/17510/pdf,semantic_scholar,,"Abstract. As a matter of fact, with the exponential growth of data, machine learning (ML) techniques have increasingly relied on distributed and parallel computing to handle large-scale problems. With this in mind, this paper provides a comparative analysis of distributed and parallel machine learni"
726,,Improving SpikeProp’s Training Efficiency in Spiking Neural Networks for Large Language Models Through Innovative Weight Initialization,Falah Y. H. Ahmed; Muhammad Zakarya; Naveed Khan; D. A. Zebari; Mahmood Al-Bahri,2025,International Journal of Computational Intelligence Systems,,,,,1,0.000,0.000,10.1007/s44196-025-00961-x,https://www.semanticscholar.org/paper/c59bda08b56271353cb1a1d036fc3e5f9a319f86,,semantic_scholar,,
727,,Early Parkinson's Disease Diagnosis using Hand-Drawn Image Patterns using Lightweight and Deep Learning Models with Explainable AI,S. Nithya; P. Shanmugavadivu,2025,2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS),,,,,0,0.000,0.000,10.1109/WorldSUAS66815.2025.11199127,https://www.semanticscholar.org/paper/54cc3c4c5ef22a3c1c12945f381b63993a4367f4,,semantic_scholar,,"Parkinson's disease (PD) is a neurological disorder characterized by subtle early-stage motor impairments, drawing considerable attention from the medical community. This research study presents a benchmarking between lightweight and deep learning convolutional neural network (CNN) models for Parkin"
728,,Optimal Convergence and Edge Efficiency Cloud Prediction for Multi-domain Lightweight Models,Chen Wang,2025,Applied and Computational Engineering,,,,,0,0.000,0.000,10.54254/2755-2721/2025.ld26179,https://www.semanticscholar.org/paper/5c14689f159aac90b70b369ff733c31010368058,,semantic_scholar,,"To address the growing demand for efficient natural language processing capabilities on resource-constrained edge devices, lightweight transformer architectures like Nano-GPT have emerged as essential solutions. However, their operational efficiency is profoundly influenced by the domain characteris"
729,,"Advancements in Diffusion Models for Image Generation: A Comparative Analysis of DDPM, LDM, and DDIM",Zixiang Jin,2024,Applied and Computational Engineering,,,,,3,0.000,0.000,10.54254/2755-2721/104/20241184,https://www.semanticscholar.org/paper/991ed537991f83e6dd01cbbc55c2b8b88a9fe4bf,https://www.ewadirect.com/proceedings/ace/article/view/16704/pdf,semantic_scholar,,"Abstract. This research provides a thorough exploration of diffusion models in image generation, comparing various methodologies to assess their efficacy and efficiency. The study begins with an introduction to foundational technologies and key concepts, progressing through an analysis of basic and "
730,,Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry,M. Bursch; J. Mewes; A. Hansen; S. Grimme,2022,Angewandte Chemie,,,,,613,0.000,0.000,10.1002/anie.202205735,https://www.semanticscholar.org/paper/e0e21f8d524720f50817a19cfb50073d8b11298d,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826355,semantic_scholar,,"Abstract Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum‐chemical calculations applies density functional theory (DFT) evaluated in atomic‐orbital"
731,,"Defining Near-Term to Long-Term Research Opportunities to Advance Metrics, Models, and Methods for Smart and Sustainable Manufacturing.",A. Raman; Karl R. Haapala; Kamyar Raoufi; B. Linke; W. Bernstein,2020,Smart and Sustainable Manufacturing Systems,,,,,10,0.000,0.000,10.1520/ssms20190047,https://www.semanticscholar.org/paper/67db92b05e5951390fe4808bfe5e166751ef5e6a,https://escholarship.org/content/qt0fk926mh/qt0fk926mh.pdf?t=rw6u2l,semantic_scholar,,"Over the past century, research has focused on continuously improving the performance of manufacturing processes and systems-often measured in terms of cost, quality, productivity, and material and energy efficiency. With the advent of smart manufacturing technologies-better production equipment, se"
732,,Comparative Evaluation of Sentiment Analysis Methods: From Traditional Techniques to Advanced Deep Learning Models,Fuhai Wang,2024,Applied and Computational Engineering,,,,,2,0.000,0.000,10.54254/2755-2721/105/2024tj0056,https://www.semanticscholar.org/paper/9be2f4dcb2cc529436848e2a87e95014d13bd3fd,https://www.ewadirect.com/proceedings/ace/article/view/16859/pdf,semantic_scholar,,"Abstract. Sentiment evaluation plays a crucial role in deciphering public perception and consumer responses in today's digital landscape. This investigation offers a thorough assessment of diverse sentiment evaluation techniques, contrasting conventional machine learning methodologies with cutting-e"
733,,Large Language Models in Drug Discovery: A Comprehensive Analysis of Drug-Target Interaction Prediction,Raghad J. AbuNasser; Mostafa Z. Ali; Yaser Jararweh; Mustafa Daraghmeh; Talal Z. Ali,2024,2024 2nd International Conference on Foundation and Large Language Models (FLLM),,,,,6,0.000,0.000,10.1109/FLLM63129.2024.10852448,https://www.semanticscholar.org/paper/a171bdc60476fc633ec9882074a7ac9d754cfb26,,semantic_scholar,,"Large Language Models have successfully caught the eyes of the pharmaceutical industry and provided aid in several tasks, such as de novo drug design, drug repurposing, molecular optimization, activity prediction, and Drug-Target Interaction (DTI) prediction. In this survey, we delved deep into thes"
734,,"Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency",E. J. Husom; Arda Goknil; Merve Astekin; Lwin Khin Shar; Andre KÃ¥sen,2025,ACM Trans. Internet Things,,,,,19,0.000,0.000,10.1145/3767742,https://www.semanticscholar.org/paper/69a1fa7bc3d0b8f006419bbf859cc0ca9bfe889a,,semantic_scholar,,"Deploying Large Language Models (LLMs) on edge devices presents significant challenges due to computational constraints, memory limitations, inference speed, and energy consumption. Model quantization has emerged as a key technique to enable efficient LLM inference by reducing model size and computa"
735,,Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning,Thomas Carta; Clément Romac; Thomas Wolf; S. Lamprier; Olivier Sigaud,2023,International Conference on Machine Learning,,,,,235,0.000,0.000,10.48550/arXiv.2302.02662,https://www.semanticscholar.org/paper/0b58f4ec8cbf6f63fb65b7e3c368cf511eadecd3,https://arxiv.org/pdf/2302.02662,semantic_scholar,,"Recent works successfully leveraged Large Language Models' (LLM) abilities to capture abstract knowledge about world's physics to solve decision-making problems. Yet, the alignment between LLMs' knowledge and the environment can be wrong and limit functional competence due to lack of grounding. In t"
736,,Underlying factors for gold price prediction based on ARIMA models,Yuntian Gu,2024,Applied and Computational Engineering,,,,,1,0.000,0.000,10.54254/2755-2721/101/20240993,https://www.semanticscholar.org/paper/931c457910b5e28249a9cc2d5d5bc48fab5aeaf8,https://www.ewadirect.com/proceedings/ace/article/view/16626/pdf,semantic_scholar,,"Abstract. The purpose of this study is to explore the application of ARIMA model and deep learning technology in time series diagram prediction and the comparison of their effects. First, this paper analyzes the time series data in detail and models them using the ARIMA model. The ARIMA model effect"
737,,Energy Considerations of Large Language Model Inference and Efficiency Optimizations,Jared Fernandez; Clara Na; Vashisth Tiwari; Yonatan Bisk; Sasha Luccioni,2025,Annual Meeting of the Association for Computational Linguistics,,,,,17,0.000,0.000,10.48550/arXiv.2504.17674,https://www.semanticscholar.org/paper/fd539b0c6279997a8b8aaf6ff1f2677cc9e011bd,,semantic_scholar,,"As large language models (LLMs) scale in size and adoption, their computational and environmental costs continue to rise. Prior benchmarking efforts have primarily focused on latency reduction in idealized settings, often overlooking the diverse real-world inference workloads that shape energy use. "
738,,Enhancing Salary Prediction Accuracy with Advanced Machine Learning Models,Qingling Bao,2024,Applied and Computational Engineering,,,,,2,0.000,0.000,10.54254/2755-2721/96/20241185,https://www.semanticscholar.org/paper/f81a7ff27db1889043f5e598e4f8d0cbb693cccf,https://www.ewadirect.com/proceedings/ace/article/view/17371/pdf,semantic_scholar,,"Abstract. Accurate salary prediction is crucial for navigating the complexities of the job market and ensuring fair compensation practices. This research focuses on evaluating advanced machine learning models to improve salary prediction accuracy. The study integrates demographic, educational, and p"
739,,Vision Language Models in Autonomous Driving: A Survey and Outlook,Xingcheng Zhou; Mingyu Liu; Ekim Yurtsever; B. L. Žagar; Walter Zimmer,2023,IEEE Transactions on Intelligent Vehicles,,,,,128,0.000,0.000,10.1109/tiv.2024.3402136,https://www.semanticscholar.org/paper/f2665e9d29836166beef6afccd9378030b352a2c,,semantic_scholar,,"The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD) have attracted widespread attention due to their outstanding performance and the ability to leverage Large Language Models (LLMs). By incorporating language data, driving systems can gain a better understanding"
740,,"Assessment of urban growth in relation to urban sprawl using landscape metrics and Shannon’s entropy model in Jalpaiguri urban agglomeration, West Bengal, India",Sanjoy Barman; Dipesh Roy; Bipul Chandra Sarkar; Hussein Almohamad; Hazam Ghassan Abdo,2024,Geocarto International,,,,,37,0.000,0.000,10.1080/10106049.2024.2306258,https://www.semanticscholar.org/paper/bc76e408b4a5d8fee2bab23fa513cdaff71d5958,https://www.tandfonline.com/doi/pdf/10.1080/10106049.2024.2306258?needAccess=true,semantic_scholar,,"Abstract The rapid urban growth and anthropogenic activities have posed a threat to the local environment and ecosystem around the world. This situation has become a hindrance to planners and policy makers for sustainable urban development. Therefore, this study mainly focuses on the assessment of u"
741,,"Comparison Distributed and Parallel Machine Learning: Evidence from Models, Principles and Application Scenarios",Zhefan Zhang,2024,Applied and Computational Engineering,,,,,0,0.000,0.000,10.54254/2755-2721/102/20241145,https://www.semanticscholar.org/paper/a186c22fb10a7f19692418b9ce8b25fa5526e1dc,https://www.ewadirect.com/proceedings/ace/article/view/16703/pdf,semantic_scholar,,"Abstract. Contemporarily, the demand for processing large-scale data has been rapidly increasing, prompting continuous advancements in the field of machine learning. This study examines the state of parallel and distributed machine learning at present, both of which aim to enhance computational effi"
742,,Comparative Analysis of Energy Efficiency Between ARM and x86 Architectures in Mobile Devices and Its Implications for Human-Computer Interaction,Geevarghese Regi; Jacob Jayan Kunnappally; Rinza Yunus,2025,Kristu Jayanti Journal of Computational Sciences (KJCS),,,,,0,0.000,0.000,10.59176/kjcs.v4i1.2434,https://www.semanticscholar.org/paper/b332a9cea1030b8964575293f4d740b7132da5ac,,semantic_scholar,,"This paper provides a comparative analysis of the energy efficiency between ARM and x86 architectures in mobile devices, emphasizing their implications for Human-Computer Interaction (HCI). Energy efficiency is a crucial factor in mobile computing, which directly affects device performance and batte"
743,,Forecast of SARIMA and ARIMA Models: An Application for Temperature Prediction,Raluca-Alexandra Oană,2025,2025 10th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE),,,,,0,0.000,0.000,10.1109/EEAE65901.2025.11273756,https://www.semanticscholar.org/paper/79e55efa0f55d8245ce0cb49db2a156e33624de1,,semantic_scholar,,The variation and the constant evolution of the weather represents a demanding task for researchers around the world. These big fluctuations in weather systems require advanced prediction algorithms. This paper is made around the use case of the Seasonal Autoregressive Integrated Moving Average (SAR
744,,"A Review of Video Object Detection: Datasets, Metrics and Methods",Haidi Zhu; Haoran Wei; Baoqing Li; Xiaobing Yuan; N. Kehtarnavaz,2020,Applied Sciences,,,,,118,0.000,0.000,10.3390/app10217834,https://www.semanticscholar.org/paper/3c03cb37863eea4be5e01f407d6899620dc4d254,https://www.mdpi.com/2076-3417/10/21/7834/pdf?version=1605146378,semantic_scholar,,"Although there are well established object detection methods based on static images, their application to video data on a frame by frame basis faces two shortcomings: (i) lack of computational efficiency due to redundancy across image frames or by not using a temporal and spatial correlation of feat"
745,,On Evaluation Metrics for Graph Generative Models,Rylee Thompson; Boris Knyazev; Elahe Ghalebi; Jungtaek Kim; Graham W. Taylor,2022,International Conference on Learning Representations,,,,,56,0.000,0.000,,https://www.semanticscholar.org/paper/410f0a0a2311c50e6dd2338f2708286ea8c87f23,,semantic_scholar,,"In image generation, generative models can be evaluated naturally by visually inspecting model outputs. However, this is not always the case for graph generative models (GGMs), making their evaluation challenging. Currently, the standard process for evaluating GGMs suffers from three critical limita"
746,,Exploring lightweight machine learning models for personal internet of things (IOT) device security,Sofiritari Ibikoroma Amgbara; Chukwuebuka Akwiwu-Uzoma; Ola David,2024,World Journal of Advanced Research and Reviews,,,,,7,0.000,0.000,10.30574/wjarr.2024.24.2.3449,https://www.semanticscholar.org/paper/1e3276c0736a8a63aaf39ea43a7786a32fbccbc7,,semantic_scholar,,"The proliferation of Internet of Things (IoT) devices in personal and household environments has led to a significant increase in security vulnerabilities. These devices, due to their limited computational resources, often struggle to support conventional security solutions, making them prime target"
747,,Improving the streamflow prediction accuracy in sparse data regions: a fresh perspective on integrated hydrological-hydrodynamic and hybrid machine learning models,Saeed Khorram; N. Jehbez,2024,Engineering Applications of Computational Fluid Mechanics,,,,,1,0.000,0.000,10.1080/19942060.2024.2387051,https://www.semanticscholar.org/paper/838d846662d0b393b278c4fd52183b171bfe0075,https://doi.org/10.1080/19942060.2024.2387051,semantic_scholar,,"ABSTRACT Considering the differences and complex nonlinear relationships of the observational data, this research integrated the hydrological, hydrodynamic and time series models, including the SWAT+, MIKE21, VMD, SARIMA, TCN and ADPSO, to increase the accuracy and efficiency of streamflow simulatio"
748,,Study on the Efficiency of Models Forecasting the Load on the Servers of a Cellular Operator,I. Semenova; R. E. Ildiyarov,2023,Mathematical Models and Computer Simulations,,,,,0,0.000,0.000,10.1134/S2070048223040154,https://www.semanticscholar.org/paper/5d316cd6ec476d07b988849aa970855ada00e648,,semantic_scholar,,
749,,Neural Machine Translation (NMT): Deep learning approaches through Neural Network Models,Junhui Hu,2024,Applied and Computational Engineering,,,,,5,0.000,0.000,10.54254/2755-2721/82/20240944,https://www.semanticscholar.org/paper/ff6cb67a94d74213bbb023048c24dfba532ec4bf,https://www.ewadirect.com/proceedings/ace/article/view/16590/pdf,semantic_scholar,,"Abstract. This paper explores the significant advancements in Neural Machine Translation (NMT) models, focusing on the impact of different architectures, training methodologies, and optimization techniques on translation quality. The study contrasts the performance of Recurrent Neural Networks (RNNs"
750,,Advancements and Applications of Large Language Models in Natural Language Processing: A Comprehensive Review,Mengchao Ren,2024,Applied and Computational Engineering,,,,,6,0.000,0.000,10.54254/2755-2721/97/20241406,https://www.semanticscholar.org/paper/1e6cada8fc3c120a512fec6cb59bdf954de82990,https://www.ewadirect.com/proceedings/ace/article/view/17680/pdf,semantic_scholar,,"Abstract. Large language models (LLMs) have revolutionized the field of natural language processing (NLP), demonstrating remarkable capabilities in understanding, generating, and manipulating human language. This comprehensive review explores the development, applications, optimizations, and challen"
751,,EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models,Zekun Wang; Minghua Ma; Zexin Wang; Rongchuan Mu; Liping Shan,2025,Annual Meeting of the Association for Computational Linguistics,,,,,4,0.000,0.000,10.48550/arXiv.2506.00479,https://www.semanticscholar.org/paper/e6dccc6c7a5dc6d2e205ed5298f3215c99c13ac1,,semantic_scholar,,"Large Vision-Language Models (LVLMs) have achieved remarkable success, yet their significant computational demands hinder practical deployment. While efforts to improve LVLM efficiency are growing, existing methods lack comprehensive evaluation across diverse backbones, benchmarks, and metrics. In t"
752,,"Automated Detection of Glaucoma using OCT RNFLT Maps and Supervised Deep Learning Models: A Comparative Study of CNN, MobileNet, ResNet50, and VGG16 Architectures",Khasim Syed; Shaik Kareemulla; Unnam Sudha Rani; Shantanu Maity,2025,2025 International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT),,,,,0,0.000,0.000,10.1109/ICICNCT66124.2025.11232589,https://www.semanticscholar.org/paper/a13ecef2b0bbc8e8d863f9b7e49cb7cf5b23a8b8,,semantic_scholar,,"Glaucoma is an important cause of irreversible blindness worldwide, with gradual degeneration of the optic nerve frequently unnoticed until serious vision impairment is present. Conventional diagnostic methods are not sensitive for early diagnosis, needing using automated means. A comparative compar"
753,,Federated Learning Optimization Using Quantum-Inspired Models for Privacy-Preserving Edge Computing in Smart Cities,B. S. Sudame; B. K; Roshan Nayak; Vengalapudi Appalakonda; Pooja Sapra,2025,2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS),,,,,0,0.000,0.000,10.1109/IACIS65746.2025.11211115,https://www.semanticscholar.org/paper/19a884b4f189520300276d19798ed720f02d857a,,semantic_scholar,,"Real time data processing on smart city infrastructure has increasingly relied on edge computing, but often at the cost of tradeoffs between computational efficiency and privacy of data. In this work, we present a novel quantum inspired federated learning framework, called QI FedLearn which takes ad"
754,,Combining Green Metrics and Digital Twins for Sustainability Planning and Governance of Smart Buildings and Cities,Casey R. Corrado; Suzanne M. DeLong; Emily G. Holt; Edward Y. Hua; A. Tolk,2022,Sustainability,,,,,37,0.000,0.000,10.3390/su142012988,https://www.semanticscholar.org/paper/cf93d40f52676b70f436c70d5f0f5584940a039a,https://www.mdpi.com/2071-1050/14/20/12988/pdf?version=1666585454,semantic_scholar,,"Creating a more sustainable world will require a coordinated effort to address the rise of social, economic, and environmental concerns resulting from the continuous growth of cities. Supporting planners with tools to address them is pivotal, and sustainability is one of the main objectives. Modelin"
755,,Optimized Assertiveness-Cost Evaluation: An Innovative Performance Measuring Method for Machine Learning Models,Lyanh Vinicios Lopes Pinto; André Vinicius Neves Alves; Adriano Madureira Dos Santos; Flávio Rafael Trindade Moura; W. Júnior,2024,Latin American Conference on Computational Intelligence,,,,,0,0.000,0.000,10.1109/LA-CCI62337.2024.10814843,https://www.semanticscholar.org/paper/027b225b5b2e83a30af80f85887cf5c437ee9734,,semantic_scholar,,"The increasing use of Machine Learning (ML) across various sectors has rendered model evaluation a progressively complex task. Ensuring models exhibit both high performance and usability necessitates in-depth evaluations of both assertiveness and computational cost. To address these needs, this stud"
756,,LLM-ProS: Analyzing Large Language Models’ Performance in Competitive Problem Solving,Md Sifat Hossain; Anika Tabassum; Md. Fahim Arefin; T. S. Zaman,2025,2025 IEEE/ACM International Workshop on Large Language Models for Code (LLM4Code),,,,,4,0.000,0.000,10.1109/LLM4Code66737.2025.00015,https://www.semanticscholar.org/paper/5791126fd69fac3dd013bc8f0609579bf3a78eaf,,semantic_scholar,,"The rapid advancement of large language models has opened new avenues for automating complex problem-solving tasks such as algorithmic coding and competitive programming. This paper introduces a novel evaluation technique, LLM-ProS, to assess the performance of state-of-the-art LLMs on International"
757,,Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data,Juanhui Li; Sreyashi Nag; Hui Liu; Xianfeng Tang; S. Sarwar,2024,North American Chapter of the Association for Computational Linguistics,,,,,5,0.000,0.000,10.48550/arXiv.2411.08028,https://www.semanticscholar.org/paper/9f1622d33fac64c06fc8bb1e518ca71ebe2730c6,,semantic_scholar,,"In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computation demands of LLMs limit their practicality in many applications, especially when further fine-tuning is required. To add"
758,,Unlocking the Planning Capabilities of Large Language Models with Maximum Diversity Fine-tuning,Wenjun Li; Changyu Chen; Pradeep Varakantham,2024,North American Chapter of the Association for Computational Linguistics,,,,,4,0.000,0.000,10.18653/v1/2025.findings-naacl.183,https://www.semanticscholar.org/paper/f9dedd58a07f24de1ebba7de35ad111f58a8ddce,,semantic_scholar,,"Large language models (LLMs) have demonstrated impressive task-solving capabilities through prompting techniques and system designs, including solving planning tasks (e.g., math proofs, basic travel planning) when sufficient data is available online and used during pre-training. However, for plannin"
759,,Artificial lemming algorithm: a novel bionic meta-heuristic technique for solving real-world engineering optimization problems,Yaning Xiao; Hao Cui; Ruba Abu Khurma; Pedro A. Castillo,2025,Artificial Intelligence Review,,,,,112,0.000,0.000,10.1007/s10462-024-11023-7,https://www.semanticscholar.org/paper/8950079471892af2fd164bc90693009c076643dc,,semantic_scholar,,
760,,AI Generated Text Detection using LORA based fine-tuning of LLM Models,Akhilesh P; Anjali Chennupati; Bhamidipati Prahas; Bommisetty Durga Jasvitha; Manju Venugopalan,2025,2025 3rd World Conference on Communication & Computing (WCONF),,,,,0,0.000,0.000,10.1109/WCONF64849.2025.11233554,https://www.semanticscholar.org/paper/f59dc249e7b194a7b8e3cbac5b35c51ba1296c7b,,semantic_scholar,,"As the increased use of sophisticated language models such as ChatGPT, Davinci, and Cohere spreads, it is becoming more difficult to differentiate machine-generated text from human-written content. This work tackles SemEval 2024 Task 8 Subtask A monolingual track, which entails multi-domain human vs"
761,,MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection,Haoyang He; Yuhu Bai; Jiangning Zhang; Qingdong He; Hongxu Chen,2024,Neural Information Processing Systems,,,,,107,0.000,0.000,10.48550/arXiv.2404.06564,https://www.semanticscholar.org/paper/e29a34d17dc41422fb16c6d8c258dfa7ff949b47,,semantic_scholar,,"Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers are burdened by quadratic computational complexity. Mamba-based models, with their superior long-range modeling and linear"
762,,Advancements in Target Detection: A Comparative Analysis of Deep Learning Models for Real-Time Applications,Tianyang Qin,2024,Applied and Computational Engineering,,,,,0,0.000,0.000,10.54254/2755-2721/81/20241096,https://www.semanticscholar.org/paper/ee2ed983021ab5b86d8c8dc682d563b9889e2b14,https://www.ewadirect.com/proceedings/ace/article/view/16689/pdf,semantic_scholar,,"Abstract. Target detection is a vital field within computer vision, playing an essential role in applications. This paper investigates the advancements and efficiencies of contemporary target detection methodologies, focusing on deep learning frameworks. Through a systematic review and evaluation of"
763,,An Intelligent Integration of Fine-Tuned DeepSeek Models for an Effective Japanese Online Education System,Lan Gao,2025,2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS),,,,,0,0.000,0.000,10.1109/IACIS65746.2025.11211058,https://www.semanticscholar.org/paper/9820242ed9228873b9e27f9ea360d301fb320533,,semantic_scholar,,"With the explosive growth of machine learning and deep learning algorithm, online education system has expanded significantly, enabling the Japanese language has become more prominent to learn with adaptive and personalized learning experiences. However, conventional online platforms supporting Japa"
764,,Evaluating Language Models for Efficient Code Generation,Jiawei Liu; Songrun Xie; Junhao Wang; Yuxiang Wei; Yifeng Ding,2024,arXiv.org,,,,,68,0.000,0.000,10.48550/arXiv.2408.06450,https://www.semanticscholar.org/paper/47e0ded22e3f446af96b41ec25c3b38f533cb489,,semantic_scholar,,"We introduce Differential Performance Evaluation (DPE), a framework designed to reliably evaluate Large Language Models (LLMs) for efficient code generation. Traditional coding benchmarks often fail to provide reliable insights into code efficiency, due to their reliance on simplistic test inputs an"
765,,LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism,Bingya Wu; Shengyu Liu; Yinmin Zhong; Peng Sun; Xuanzhe Liu,2024,Symposium on Operating Systems Principles,,,,,110,0.000,0.000,10.1145/3694715.3695948,https://www.semanticscholar.org/paper/eb06e95dd3eb5a916e52d2e463f474ef4967d8ca,https://dl.acm.org/doi/pdf/10.1145/3694715.3695948,semantic_scholar,,"The context window of large language models (LLMs) is rapidly increasing, leading to a huge variance in resource usage between different requests as well as between different phases of the same request. Restricted by static parallelism strategies, existing LLM serving systems cannot efficiently util"
766,,Federated Learning for IoT Networks: Enhancing Efficiency and Privacy,Sofia Zahri; Hajar Bennouri; Abdellah Chehri; A. M. Abdelmoniem,2023,World Forum on Internet of Things,,,,,2,0.000,0.000,10.1109/WF-IoT58464.2023.10539528,https://www.semanticscholar.org/paper/2ccc4ce0731f72759ecad272f24f5e6d496d7fde,,semantic_scholar,,"In today's world, the rapid expansion of IoT networks and the proliferation of smart devices in our daily lives, have resulted in the generation of substantial amounts of heterogeneous data. To handle this data effectively, advanced data processing technologies are necessary to guarantee the preserv"
767,,M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems,Zeyu Cui; Jianxin Ma; Chang Zhou; Jingren Zhou; Hongxia Yang,2022,arXiv.org,,,,,250,0.000,0.000,10.48550/arXiv.2205.08084,https://www.semanticscholar.org/paper/cbf3bf8f541f5b446c59c8deacbcc18527768c75,https://arxiv.org/pdf/2205.08084,semantic_scholar,,"Industrial recommender systems have been growing increasingly complex, may involve \emph{diverse domains} such as e-commerce products and user-generated contents, and can comprise \emph{a myriad of tasks} such as retrieval, ranking, explanation generation, and even AI-assisted content production. Th"
768,,AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions,F. Bonnet; Jocelyn Ahmed Mazari; P. Cinnella; P. Gallinari,2022,Neural Information Processing Systems,,,,,80,0.000,0.000,10.48550/arXiv.2212.07564,https://www.semanticscholar.org/paper/e8ca130df3f62798fbf432982e67aa93a5561a76,http://arxiv.org/pdf/2212.07564,semantic_scholar,,"Surrogate models are necessary to optimize meaningful quantities in physical dynamics as their recursive numerical resolutions are often prohibitively expensive. It is mainly the case for fluid dynamics and the resolution of Navier-Stokes equations. However, despite the fast-growing field of data-dr"
769,,Intrusion Detection in the Internet of Vehicles Using Transformer Models,Mohammad Alauthman; Ashraf S. Mashaleh; Nauman Aslam; A. Aldweesh; Ammar Almomani,2025,2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA),,,,,0,0.000,0.000,10.1109/ICCIAA65327.2025.11013054,https://www.semanticscholar.org/paper/58f0abd59fd268674bc066ee7c8bc15e4cade1a2,,semantic_scholar,,"The proliferation of Internet of Vehicles (IoV) systems has introduced critical cybersecurity vulnerabilities in connected vehicle infrastructures. This paper presents a novel application of Transformer architecture for intrusion detection in vehicular Controller Area Network (CAN) buses, specifical"
770,,Simplifying AI reasoning: unlocking logical capabilities in large language models (LLMs),Peraschi Selvan; Subramanian,2025,World Journal of Advanced Research and Reviews,,,,,0,0.000,0.000,10.30574/wjarr.2025.26.2.1808,https://www.semanticscholar.org/paper/dccbc8168c2ba8e163d773b77c7320d0535bc9a1,,semantic_scholar,,"The integration of logical reasoning capabilities in large language models (LLMs) represents a transformative advancement in artificial intelligence, fundamentally altering the landscape of machine intelligence. This article examines how LLMs have evolved from pattern recognition systems into sophis"
771,,Mercury: An Efficiency Benchmark for LLM Code Synthesis,Mingzhe Du; A. Luu; Bin Ji; See-Kiong Ng,2024,arXiv.org,,,,,22,0.000,0.000,10.48550/arXiv.2402.07844,https://www.semanticscholar.org/paper/15dc4534ae1e5aefdc196cf1da983b2ee56c1dda,,semantic_scholar,,
772,,Enhancing machine learning models: addressing challenges and future directions,Sateesh kumar Rongali,2025,World Journal of Advanced Research and Reviews,,,,,3,0.000,0.000,10.30574/wjarr.2025.25.1.0190,https://www.semanticscholar.org/paper/b9ce00d1227b8fec502052f63d295c8bc500d9b5,,semantic_scholar,,"Machine learning is considered as a core of modern artificial intelligence with progressive advancements throughout a spectrum including but not limited to healthcare and finance, natural language processing and self-driving cars. However, several problems remain to affect the efficiency, equal oppo"
773,,Rationale-Guided Distillation for E-Commerce Relevance Classification: Bridging Large Language Models and Lightweight Cross-Encoders,Sanjay Agrawal; Faizan Ahemad; Vivek Sembium,2025,International Conference on Computational Linguistics,,,,,3,0.000,0.000,,https://www.semanticscholar.org/paper/306bbb8a7c3945b543b81438902a798488c6ef09,,semantic_scholar,,
774,,Towards the Standardization of Energy Efficiency Metrics of the AI Lifecycle in 6G and Beyond,Shih-Kai Chou; Jernej Hribar; M. Mohorčič; Carolina Fortuna,2024,IEEE Conference on Standards for Communications and Networking,,,,,3,0.000,0.000,10.1109/CSCN63874.2024.10849732,https://www.semanticscholar.org/paper/75eb1fdfd7e0c9ac0b2a5b063f94b6fa5d18e190,,semantic_scholar,,"As 6G networks become Artificial Intelligence (AI)native, measuring energy efficiency becomes increasingly complex due to the computational demands of AI integration. Traditional metrics, such as Energy-per-Bit, only capture communication efficiency and overlook the energy costs of AI-driven systems"
775,,Efficiency metrics for ocean alkalinity enhancements under responsive and prescribed atmospheric pCO2 conditions,Michael D. Tyka,2025,Biogeosciences,,,,,7,0.000,0.000,10.5194/bg-22-341-2025,https://www.semanticscholar.org/paper/bcd30dc66349d106a6cbb5bc1993ffde964a0729,,semantic_scholar,,"Abstract. Ocean alkalinity enhancement (OAE) and direct ocean removal (DOR) are emerging as promising technologies for enacting negative emissions. The long equilibration timescales, potential for premature subduction of surface water parcels, and extensive horizontal transport and dilution of added"
776,,Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs,D. Narayanan; Keshav Santhanam; Peter Henderson; Rishi Bommasani; Tony Lee,2023,arXiv.org,,,,,3,0.000,0.000,10.48550/arXiv.2305.02440,https://www.semanticscholar.org/paper/d4d7966a7b4dbf4cd764e443392d22826618a293,http://arxiv.org/pdf/2305.02440,semantic_scholar,,"Large language models (LLMs) power many state-of-the-art systems in natural language processing. However, these models are extremely computationally expensive, even at inference time, raising the natural question: when is the extra cost of deploying a larger model worth the anticipated boost in capa"