Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure
The paper says better spreadsheet Q&A depends on preserving the grid’s structure, not just retrieving better chunks.
Zofia Smoleń proposes splitting spreadsheets into interpretable chunks by annotating cell roles for LLM-based RAG. The framework beats prior approaches, but the abstract says it still hits a ceiling because spreadsheet meaning is two-dimensional and not cleanly reducible to fixed cell classes. The paper argues that even human-level annotation cannot fully capture the range of structural relationships in a grid. Its proposed direction is to flatten spreadsheets into text through dimensionality-reduction methods rather than discrete classification. ArXiv · AI/CL/LG's note
Zofia Smoleń proposes splitting spreadsheets into interpretable chunks by annotating cell roles for LLM-based RAG. The framework beats prior approaches, but the abstract says it still hits a ceiling because spreadsheet meaning is two-dimensional and not cleanly reducible to fixed cell classes. The paper argues that even human-level annotation cannot fully capture the range of structural relationships in a grid. Its proposed direction is to flatten spreadsheets into text through dimensionality-reduction methods rather than discrete classification. ArXiv · AI/CL/LG's note
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