{"url":"/dataset/sheetcopilot","name":"SheetCopilot","full_name":null,"description_markdown":"The SheetCopilot dataset contains 28 evaluation workbooks and 221 spreadsheet manipulation tasks that are applied to these workbooks. These tasks involve diverse atomic actions related to six task categories (i.e. Entry and manipulation, Formatting, Management, Charts, Pivot Table, and Formula).\r\n\r\nDataset statistics:\r\n\r\n1. Each task possesses one or more ground truth solutions.\r\n\r\n2. The lengths of the task instructions range from 20 to 530 characters, with most tasks between 80 and 110 characters.\r\n\r\n3. The number of atomic actions required by each task ranges from 1 to 9.\r\n\r\nEvaluation metrics:\r\n\r\n1. Execution success rate, pass rate, and the number of used actions are evaluated to judge the functional correctness and efficiency of a method.\r\n\r\n2. A submitted solution is considered correct if the properties to be checked match those of any of the GT solutions of the corresponding task.\r\n\r\nPlease download the full datasets in our Github Repo:\r\n\r\nhttps://github.com/BraveGroup/SheetCopilot\r\n\r\nThanks for using our dataset!","description_withheld":null,"homepage":"https://sheetcopilot.github.io/","introduced_date":"2023-05-29","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Tables","url":"/datasets/modality/tables"}],"tasks":[{"name":"Robot Task Planning","url":"/task/robot-task-planning","datasets_with_task":"/datasets/task/robot-task-planning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SheetCopilot"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/robot-task-planning-on-sheetcopilot","task":"Robot Task Planning","dataset_variant":"SheetCopilot","rows":2,"metrics":["Pass@1"],"first_row_in_archive_order":{"model":"SheetAgent (GPT-3.5)","paper":"/paper/sheetagent-a-generalist-agent-for-spreadsheet","metrics":{"Pass@1":"61.1%"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/sheetagent-a-generalist-agent-for-spreadsheet","title":"SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models","date":"2024-03-06","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/sheetcopilot-bringing-software-productivity","title":"SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models","date":"2023-05-30","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}