Temporal Event Sequences
Collection
A collection of real-world temporal event sequences from multiple domains. • 6 items • Updated • 2
Dataset Viewer
The dataset viewer is not available for this dataset.
The JWT signature verification failed. Check the signing key and the algorithm.
Error code: JWTInvalidSignature
Exception: InvalidSignatureError
Message: Signature verification failed
Traceback: Traceback (most recent call last):
File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
decoded = jwt.decode(
jwt=token,
...<2 lines>...
options=options,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
decoded = self.decode_complete(
jwt,
...<8 lines>...
leeway=leeway,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
decoded = self._jws.decode_complete(
jwt,
...<3 lines>...
detached_payload=detached_payload,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
self._verify_signature(
~~~~~~~~~~~~~~~~~~~~~~^
signing_input,
^^^^^^^^^^^^^^
...<4 lines>...
options=merged_options,
^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
raise InvalidSignatureError("Signature verification failed")
jwt.exceptions.InvalidSignatureError: Signature verification failedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
NYC Taxi Trip Dataset
This dataset contains NYC taxi trip data from May 1-7, 2013, excluding trips to and from Staten Island. It includes 2,957 sequences with 362,374 events and 8 location types. The data can be downloaded from NYC Taxi Trips and is subject to the NYC Terms of Use. The detailed data preprocessing steps used to create this dataset can be found in the TPP-LLM paper and TPP-Embedding paper.
Update (2025-10-28): Added three timestamp fields (timestamp_event, timestamp_since_start, timestamp_since_last_event) in seconds, and corrected the geographic boundary from v24C to the historically accurate 2013 version (v13B). If you wish to reproduce the original TPP-LLM results, please refer to the earlier dataset snapshots in the Commit History.
If you find this dataset useful, we kindly invite you to cite the following papers:
@article{liu2024tppllmm,
title={TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models},
author={Liu, Zefang and Quan, Yinzhu},
journal={arXiv preprint arXiv:2410.02062},
year={2024}
}
@article{liu2024retrieval,
title={Retrieval of Temporal Event Sequences from Textual Descriptions},
author={Liu, Zefang and Quan, Yinzhu},
journal={arXiv preprint arXiv:2410.14043},
year={2024}
}
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