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--- |
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license: cc-by-3.0 |
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tags: |
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- agent |
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- workflow |
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- multimodal |
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- spreadsheet |
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- pdf |
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- image |
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- code |
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- finance |
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- accouning |
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modalities: |
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- text |
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- spreadsheet |
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- pdf |
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- image |
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- code |
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configs: |
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- config_name: Finch_Dataset_All |
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data_files: |
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- split: test |
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path: |
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- finch_workflows_test.jsonl |
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--- |
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# Finch: Benchmarking Finance & Accounting across Spreadsheet-Centric Enterprise Workflows |
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This repository contains the dataset for **Finch**, an enterprise-grade benchmark for evaluating an agent’s ability to work like a skilled finance & accounting expert (work IQ) on real-world professionel workflows. |
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* **Paper**: _to be added_ |
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* **Project Page**: https://huggingface.co/datasets/FinWorkBench/Finch |
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* **Code**: https://github.com/FinWorkBench |
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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 corporations in the EUSES Corpus, investment and securities companies, World Bank, Canadian/British government agencies, and more), 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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1. **Inducing workflow types and instances** from real collaborative context in **enterprise email threads** (Enron Corpus: 500,000 emails from 150 executives and employees). |
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2. **Deriving concrete workflow instances** by analyzing changes across **spreadsheet versions** (15,000 versioned spreadsheets from Enron and EUSES) and designing workflows based on high-quality artifacts from investment and securities companies, World Bank, Canadian/British government agencies, WideSearch, Dabstep, and more. |
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3. **Conductin meticulous expert annotation** of task instructions, input files, and reference outputs, involving hundreds of hours of expert work. |
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This process yields **172 enterprise-grade workflows—primarily multi-task composite**, involving 1,710 spreadsheets and 27 million cells, capturing the intrinsic **compositional, messy, multimodal, and collaborative nature** of real-world finance & accounting work. In this release, we provide full annotations for the first 72 workflows, with the remaining 100 to be released in a subsequent update. |
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Experiment results show that even frontier agents (GPT 5.1 Pro and Claude Sonnet 4.5 Pro) solve fewer than 40% of the workflows, revealing a substantial performance gap for real-world enterprise scenarios. |
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--- |
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## 📁 Dataset Structure |
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The instruction-tuning corpus is released in **JSONL** format. |
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Each line corresponds to one **workflow-centric example**: |
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```json |
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{ |
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"id": "<workflow identifier>", |
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"instruction_en": "<English task instruction for a finance & accounting workflow>", |
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"source_files": ["<input file name>", "..."], |
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"source_files_urls": ["<input file download URL>", "..."], |
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"reference_outputs": { |
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"files": ["<reference output file name>"], |
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"text": "<textual reference output>" |
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}, |
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"reference_file_urls": ["<reference output file download URL>"], |
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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! |
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**📧 Contact:** finworkbench@gmail.com |
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