{"url":"/dataset/formulanet","name":"FormulaNet","full_name":null,"description_markdown":"# FormulaNet\r\n\r\nFormulaNet is a new large-scale Mathematical Formula Detection dataset. It consists of 46'672 pages of STEM documents from [arXiv](arxiv.org) and has \r\n13 types of labels. The dataset is split into a [train](Dataset/train) set of 44'338 pages and a [validation](Dataset/val) set of 2'334 pages. Due to \r\ncopyrights reasons, we can only provide the [list](urls.txt) of papers, which must be downloaded and processed.\r\n\r\n## Labels\r\n\r\n* inline formulae\r\n* display formulae\r\n* headers\r\n* tables\r\n* figures\r\n* paragraphs\r\n* captions\r\n* footnotes\r\n* lists\r\n* bibliographies\r\n* display formulae reference number\r\n* display formulae with reference number\r\n* footnote reference number","description_withheld":null,"homepage":"https://github.com/felix-schmitt/FormulaNet","introduced_date":"2022-08-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/formulanet-a-benchmark-dataset-for","title":"FormulaNet: A Benchmark Dataset for Mathematical Formula Detection","first_author":"Felix M. Schmitt-Koopmann","url":null},"license":{"name":"CC-BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FormulaNet"],"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":"2026-09-24T18:15:14+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."}