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@@ -39,14 +39,15 @@ This repository contains the dataset for **Finch**, an enterprise-level benchmar
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  ## Dataset Description
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- Finch focuses on **composite finance & accounting workflows** that span:
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  > data entry/import, structuring/formatting, web search, cross-sheet/file retrieval, calculation, financial modeling, validation, translation, visualization, and reporting.
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- The workflows are derived from **real-world enterprise workspaces** (Enron and various institutions/companies such as World Bank, Canada/Australia goverment, etc), including:
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  - Large and messy **spreadsheets** with multimodal artifacts including text, tables, formulas, charts, pivots, images, etc
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- - Linked **PDFs and documents** that provide additional business context
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  We adopt a three-step workflow labeling process:
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@@ -79,3 +80,9 @@ Each line corresponds to one **workflow-centric example**:
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  "task_type": "<task category (e.g., reporting, modeling)>",
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  "business_type": "<business domain (e.g., budgeting, trading)>"
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  }
 
 
 
 
 
 
 
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  ## Dataset Description
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+ Finch focuses on **messy and long-horizon finance & accounting workflows** that span:
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  > data entry/import, structuring/formatting, web search, cross-sheet/file retrieval, calculation, financial modeling, validation, translation, visualization, and reporting.
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+ The workflows are derived from **real-world enterprise workspaces** (primarily Enron, as well as World Bank, Canadian/Australian government agencies, and other corporations), including:
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+ - Enterprise **email threads** where collaborators naturally describe, discuss, and track workflows
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  - Large and messy **spreadsheets** with multimodal artifacts including text, tables, formulas, charts, pivots, images, etc
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+ - Interlinked **PDFs and documents** that provide additional business context
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  We adopt a three-step workflow labeling process:
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  "task_type": "<task category (e.g., reporting, modeling)>",
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  "business_type": "<business domain (e.g., budgeting, trading)>"
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  }
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+
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+ ---
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+ ## 📣 Feedback & Issues
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+ If you find any issues with the dataset or have suggestions, please open a discussion in the **Community** tab — we value your feedback!