Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning
Spreadsheets are central to real-world applications such as enterprise reporting, auditing, and scientific data management. Despite their ubiquity, existing large language model based approaches typically treat tables as plain text, overlooking critical layout cues and visual semantics. Moreover, real-world spreadsheets are often massive in scale, exceeding the input length that LLMs can efficiently process. To address these challenges, we propose SpreadsheetAgent, a two-stage multi-agent framework for spreadsheet understanding that adopts a step-by-step reading and reasoning paradigm. Instead of loading the entire spreadsheet at once, SpreadsheetAgent incrementally interprets localized r...
| Authors | Houxing Ren, Mingjie Zhan, Zimu Lu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
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