SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks
We consider the task of end-to-end spreadsheet generation, where language models produce spreadsheet artifacts to satisfy users' explicit and implicit constraints, specified in natural language. We introduce SpreadsheetArena, a platform for evaluating models' performance on the task via blind pairwise preference votes of LLM-generated spreadsheet workbooks. As with other complex, open-ended tasks, relevant evaluation criteria can vary greatly across use cases, often in ways that are difficult to formalize. Compared to general dialogue or text generation settings, spreadsheet generation presents unique challenges and opportunities: the task output structure is well-defined and multi-dimens...
| Authors | Srivatsa Kundurthy, Clara Na, Michael Handley et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 February 2026 |
| Last updated at source | 2 July 2026 |
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