{"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/unified-open-domain-question-answering-with","title":"UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering","arxiv_id":"2012.14610","date":"2020-12-29","proceeding":"Findings (NAACL) 2022 7","authors":["Barlas Oguz","Xilun Chen","Vladimir Karpukhin","Stan Peshterliev","Dmytro Okhonko","Michael Schlichtkrull","Sonal Gupta","Yashar Mehdad","Scott Yih"],"abstract":"We study open-domain question answering with structured, unstructured and semi-structured knowledge sources, including text, tables, lists and knowledge bases. Departing from prior work, we propose a unifying approach that homogenizes all sources by reducing them to text and applies the retriever-reader model which has so far been limited to text sources only. Our approach greatly improves the results on knowledge-base QA tasks by 11 points, compared to latest graph-based methods. More importantly, we demonstrate that our unified knowledge (UniK-QA) model is a simple and yet effective way to combine heterogeneous sources of knowledge, advancing the state-of-the-art results on two popular question answering benchmarks, NaturalQuestions and WebQuestions, by 3.5 and 2.6 points, respectively. The code of UniK-QA is available at: https://github.com/facebookresearch/UniK-QA.","url_abs":"https://arxiv.org/abs/2012.14610v3","url_pdf":"https://arxiv.org/pdf/2012.14610v3.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":"unified-open-domain-question-answering-with","repo_url":"https://github.com/facebookresearch/UniK-QA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"knowledge-base-question-answering","task_name":"Knowledge Base Question Answering"},{"task_slug":"open-domain-question-answering","task_name":"Open-Domain Question Answering"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/knowledge-base-question-answering-on-1","task":"Knowledge Base Question Answering","dataset":"WebQuestionsSP","model":"UniK-QA (T5-large)","rank_in_archive_order":4,"of":8,"metrics":{"Hits@1":"79.1"},"uses_additional_data":false},{"leaderboard":"/sota/knowledge-base-question-answering-on-1","task":"Knowledge Base Question Answering","dataset":"WebQuestionsSP","model":"UniK-QA (T5-base)","rank_in_archive_order":5,"of":8,"metrics":{"Hits@1":"76.7"},"uses_additional_data":false},{"leaderboard":"/sota/open-domain-question-answering-on-natural","task":"Open-Domain Question Answering","dataset":"Natural Questions","model":"UniK-QA","rank_in_archive_order":3,"of":5,"metrics":{"Exact Match":"54.9"},"uses_additional_data":false},{"leaderboard":"/sota/open-domain-question-answering-on-tqa","task":"Open-Domain Question Answering","dataset":"TQA","model":"UniK-QA","rank_in_archive_order":1,"of":2,"metrics":{"Exact Match":"65.5"},"uses_additional_data":false},{"leaderboard":"/sota/open-domain-question-answering-on","task":"Open-Domain Question Answering","dataset":"WebQuestions","model":"UniK-QA","rank_in_archive_order":1,"of":4,"metrics":{"Exact Match":"57.7"},"uses_additional_data":true},{"leaderboard":"/sota/question-answering-on-natural-questions-long","task":"Question Answering","dataset":"Natural Questions (long)","model":"UniK-QA","rank_in_archive_order":11,"of":13,"metrics":{"EM":"54.9"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-tiq","task":"Question Answering","dataset":"TIQ","model":"Unik-Qa","rank_in_archive_order":3,"of":9,"metrics":{"P@1":"42.5"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2012.14610","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}