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With the evolution of Large Language Models (LLMs) we can solve increasinglymore complex NLP tasks across various domains, including spreadsheets. Thiswork investigates whether LLMs can generate code (Excel OfficeScripts, aTypeScript API for executing many tasks in Excel) that solves Excel specifictasks provided via natural language user instructions. To do so we introduce anew large-scale benchmark, InstructExcel, created by leveraging the 'Automate'feature in Excel to automatically generate OfficeScripts from users' actions.Our benchmark includes over 10k samples covering 170+ Excel operations across2,000 publicly available Excel spreadsheets. Experiments across variouszero-shot and few-shot settings show that InstructExcel is a hard benchmark forstate of the art models like GPT-4. We observe that (1) using GPT-4 overGPT-3.5, (2) providing more in-context examples, and (3) dynamic prompting canhelp improve performance on this benchmark.

InstructExcel: A Benchmark for Natural Language Instruction in Excel