March 7, 2024, 5:42 a.m. | Yibin Chen, Yifu Yuan, Zeyu Zhang, Yan Zheng, Jinyi Liu, Fei Ni, Jianye Hao

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.03636v1 Announce Type: cross
Abstract: Spreadsheet manipulation is widely existing in most daily works and significantly improves working efficiency. Large language model (LLM) has been recently attempted for automatic spreadsheet manipulation but has not yet been investigated in complicated and realistic tasks where reasoning challenges exist (e.g., long horizon manipulation with multi-step reasoning and ambiguous requirements). To bridge the gap with the real-world requirements, we introduce $\textbf{SheetRM}$, a benchmark featuring long-horizon and multi-category tasks with reasoning-dependent manipulation caused by real-life …

agent arxiv cs.ai cs.lg language language models large language large language models manipulation reasoning spreadsheet type via

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