{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/race-large-scale-reading-comprehension","title":"RACE: Large-scale ReAding Comprehension Dataset From Examinations","arxiv_id":"1704.04683","date":"2017-04-15","proceeding":"EMNLP 2017 9","authors":["Guokun Lai","Qizhe Xie","Hanxiao Liu","Yiming Yang","Eduard Hovy"],"abstract":"We present RACE, a new dataset for benchmark evaluation of methods in the\nreading comprehension task. Collected from the English exams for middle and\nhigh school Chinese students in the age range between 12 to 18, RACE consists\nof near 28,000 passages and near 100,000 questions generated by human experts\n(English instructors), and covers a variety of topics which are carefully\ndesigned for evaluating the students' ability in understanding and reasoning.\nIn particular, the proportion of questions that requires reasoning is much\nlarger in RACE than that in other benchmark datasets for reading comprehension,\nand there is a significant gap between the performance of the state-of-the-art\nmodels (43%) and the ceiling human performance (95%). We hope this new dataset\ncan serve as a valuable resource for research and evaluation in machine\ncomprehension. The dataset is freely available at\nhttp://www.cs.cmu.edu/~glai1/data/race/ and the code is available at\nhttps://github.com/qizhex/RACE_AR_baselines.","url_abs":"http://arxiv.org/abs/1704.04683v5","url_pdf":"http://arxiv.org/pdf/1704.04683v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"race-large-scale-reading-comprehension","repo_url":"https://github.com/PKU-TANGENT/GAReader-LiveQA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"race-large-scale-reading-comprehension","repo_url":"https://github.com/artiom-zayats/docqa_squad","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"}],"methods":[],"datasets_introduced":[{"slug":"race","name":"RACE","full_name":"ReAding Comprehension dataset from Examinations"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1704.04683","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}