SheetCompass: A Graph-Guided Agentic Framework for Spreadsheet Reasoning

A recent study introduces SheetCompass, a framework that leverages graph guidance and memory to enhance automated spreadsheet reasoning in large language models (LLMs). Titled 'SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning,' this paper has been submitted to arXiv in the Computer Science > Artificial Intelligence section. The authors contend that current approaches simplify the complex structure of spreadsheets into linear strings, thereby neglecting essential intra-sheet boundaries and inter-sheet semantics, which hinders LLMs from utilizing the global spatial context that human experts rely on. SheetCompass effectively models structural relationships within and between worksheets while retaining task-relevant information in memory, allowing for improved reasoning over intricate workbooks. The framework tackles challenges like implicit cross-table associations, detailed column dependencies, and complex spatial arrangements. The paper can be accessed at https://arxiv.org/abs/2608.14452 and includes references, citations, and bibliographic tools, along with submission history and browsing context. This research advances AI and machine learning, particularly in spreadsheet automation and reasoning.