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arXiv · 2608.14452

SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning

Panjing He·Mingyue Cheng·Yucong Luo·Li Li·Xiaohan Zhang
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Abstract

Spreadsheets are widely used to organize, analyze, and manipulate semi-structured data, yet automated spreadsheet reasoning remains challenging for large language models (LLMs). Real-world workbooks often contain implicit cross-table associations, fine-grained column dependencies, and complex spatial layouts. Existing methods typically flatten these multidimensional structures into sequential strings, losing important intra-sheet boundaries and inter-sheet semantics. Consequently, LLMs cannot exploit the global spatial context that human experts naturally use when inspecting spreadsheets. We propose SheetCompass, a graph-guided and memory-driven agentic framework for spreadsheet reasoning and automation. SheetCompass explicitly models structural relationships within and across worksheets while maintaining task-relevant information in memory, enabling agents to reason more effectively over complex workbooks.

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Panjing He, Mingyue Cheng, Yucong Luo, Li Li, Xiaohan Zhang. 2026-08-14. SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning. https://arxiv.org/abs/2608.14452

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