{"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/a-co-matching-model-for-multi-choice-reading","title":"A Co-Matching Model for Multi-choice Reading Comprehension","arxiv_id":"1806.04068","date":"2018-06-11","proceeding":"ACL 2018 7","authors":["Shuohang Wang","Mo Yu","Shiyu Chang","Jing Jiang"],"abstract":"Multi-choice reading comprehension is a challenging task, which involves the\nmatching between a passage and a question-answer pair. This paper proposes a\nnew co-matching approach to this problem, which jointly models whether a\npassage can match both a question and a candidate answer. Experimental results\non the RACE dataset demonstrate that our approach achieves state-of-the-art\nperformance.","url_abs":"http://arxiv.org/abs/1806.04068v1","url_pdf":"http://arxiv.org/pdf/1806.04068v1.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":"a-co-matching-model-for-multi-choice-reading","repo_url":"https://github.com/shuohangwang/comatch","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1806.04068","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}