Visual-TableQA is a new open-domain benchmark of rendered table images and complex QA pairs created via multi-LLM collaborative generation, with fine-tuned models showing robust generalization to external tests.
Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj, Mustafa Canim, Michael R
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SpreadsheetAgent uses incremental multi-format reading, structural sketching, and verification to raise spreadsheet benchmark accuracy from 35.27% to 38.16%.
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Visual-TableQA: Open-Domain Benchmark for Reasoning over Table Images
Visual-TableQA is a new open-domain benchmark of rendered table images and complex QA pairs created via multi-LLM collaborative generation, with fine-tuned models showing robust generalization to external tests.
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Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning
SpreadsheetAgent uses incremental multi-format reading, structural sketching, and verification to raise spreadsheet benchmark accuracy from 35.27% to 38.16%.