{"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/answering-complex-open-domain-questions-with","title":"Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval","arxiv_id":"2009.12756","date":"2020-09-27","proceeding":"ICLR 2021 1","authors":["Wenhan Xiong","Xiang Lorraine Li","Srini Iyer","Jingfei Du","Patrick Lewis","William Yang Wang","Yashar Mehdad","Wen-tau Yih","Sebastian Riedel","Douwe Kiela","Barlas Oğuz"],"abstract":"We propose a simple and efficient multi-hop dense retrieval approach for answering complex open-domain questions, which achieves state-of-the-art performance on two multi-hop datasets, HotpotQA and multi-evidence FEVER. Contrary to previous work, our method does not require access to any corpus-specific information, such as inter-document hyperlinks or human-annotated entity markers, and can be applied to any unstructured text corpus. Our system also yields a much better efficiency-accuracy trade-off, matching the best published accuracy on HotpotQA while being 10 times faster at inference time.","url_abs":"https://arxiv.org/abs/2009.12756v2","url_pdf":"https://arxiv.org/pdf/2009.12756v2.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":"answering-complex-open-domain-questions-with","repo_url":"https://github.com/facebookresearch/multihop_dense_retrieval","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-hotpotqa","task":"Question Answering","dataset":"HotpotQA","model":"Recursive Dense Retriever","rank_in_archive_order":14,"of":72,"metrics":{"ANS-EM":"0.623","ANS-F1":"0.753","JOINT-EM":"0.418","JOINT-F1":"0.666","SUP-EM":"0.575","SUP-F1":"0.809"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2009.12756","atlas_url":"https://app.syntology.ai/?focus=2009.12756","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}