{"url":"/dataset/acl-title-and-abstract-dataset","name":"ACL Title and Abstract Dataset","full_name":null,"description_markdown":"This dataset gathers 10,874 title and abstract pairs from the ACL Anthology Network (until 2016).\r\n\r\nThe structure of the data is as follows:\r\n-\ttitle\r\n-\tabstract\r\n-\t\\newline\r\n\r\nThis dataset is used in our published paper:\r\nPaper Abstract Writing through Editing Mechanism\r\n\r\n## Citation\r\n```\r\n@inproceedings{wang-etal-2018-paper,\r\n    title = \"Paper Abstract Writing through Editing Mechanism\",\r\n    author = \"Wang, Qingyun  and\r\n      Zhou, Zhihao  and\r\n      Huang, Lifu  and\r\n      Whitehead, Spencer  and\r\n      Zhang, Boliang  and\r\n      Ji, Heng  and\r\n      Knight, Kevin\",\r\n    booktitle = \"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)\",\r\n    month = jul,\r\n    year = \"2018\",\r\n    address = \"Melbourne, Australia\",\r\n    publisher = \"Association for Computational Linguistics\",\r\n    url = \"https://www.aclweb.org/anthology/P18-2042\",\r\n    doi = \"10.18653/v1/P18-2042\",\r\n    pages = \"260--265\",\r\n    abstract = \"We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract. We design a novel Writing-editing Network that can attend to both the title and the previously generated abstract drafts and then iteratively revise and polish the abstract. With two series of Turing tests, where the human judges are asked to distinguish the system-generated abstracts from human-written ones, our system passes Turing tests by junior domain experts at a rate up to 30{\\%} and by non-expert at a rate up to 80{\\%}.\",\r\n}\r\n```","description_withheld":null,"homepage":"https://github.com/EagleW/ACL_titles_abstracts_dataset","introduced_date":"2018-05-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/paper-abstract-writing-through-editing","title":"Paper Abstract Writing through Editing Mechanism","first_author":"Qingyun Wang","url":null},"license":{"name":"MIT License","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Paper generation","url":"/task/paper-generation","datasets_with_task":"/datasets/task/paper-generation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ACL Title and Abstract Dataset"],"data_loaders":[{"repo":"https://github.com/EagleW/ACL_titles_abstracts_dataset","url":"https://github.com/EagleW/ACL_titles_abstracts_dataset","frameworks":[]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/paper-generation-on-acl-title-and-abstract","task":"Paper generation","dataset_variant":"ACL Title and Abstract Dataset","rows":1,"metrics":["METEOR","ROUGE-L"],"first_row_in_archive_order":{"model":"Writing-editing Network","paper":"/paper/paper-abstract-writing-through-editing","metrics":{"METEOR":"14.0","ROUGE-L":"20.3"},"code_links":[{"title":"EagleW/Writing-editing-Network","url":"https://github.com/EagleW/Writing-editing-Network"},{"title":"EagleW/ACL_titles_abstracts_dataset","url":"https://github.com/EagleW/ACL_titles_abstracts_dataset"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/paper-abstract-writing-through-editing","title":"Paper Abstract Writing through Editing Mechanism","date":"2018-05-15","rows_on_this_dataset":1,"code_links":2,"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."}