{"url":"/dataset/merger-agreement-understanding-dataset-maud","name":"Merger Agreement Understanding Dataset (MAUD)","full_name":null,"description_markdown":"MAUD is an expert-annotated merger agreement reading comprehension dataset based on the American Bar Association's 2021 Public Target Deal Points study, where lawyers and law students answered 92 questions about 152 merger agreements.\r\n\r\nWith over 39,000 examples and 47,000 total annotations, it is the largest expert-annotated legal reading comprehension dataset in the English language, as well as the first expert-annotated merger agreement dataset.","description_withheld":null,"homepage":"https://www.atticusprojectai.org/maud","introduced_date":"2023-01-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/maud-an-expert-annotated-legal-nlp-dataset","title":"MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding","first_author":"Steven H. Wang","url":null},"license":{"name":"CC BY 4.0 license","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Machine Reading Comprehension","url":"/task/machine-reading-comprehension","datasets_with_task":"/datasets/task/machine-reading-comprehension"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Merger Agreement Understanding Dataset (MAUD)"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}