{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:56:37Z","timestamp":1781196997499,"version":"3.54.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684369","type":"print"},{"value":"9781643684376","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,28]]},"abstract":"<jats:p>Supplying data augmentation to conversational question answering (CQA) can effectively improve model performance. However, there is less improvement from single-turn datasets in CQA due to the distribution gap between single-turn and multi-turn datasets. On the other hand, while numerous single-turn datasets are available, we have not utilized them effectively. To solve this problem, we propose a novel method to convert single-turn datasets to multi-turn datasets. The proposed method consists of three parts, namely, a QA pair Generator, a QA pair Reassembler, and a question Rewriter. Given a sample consisting of context and single-turn QA pairs, the Generator obtains candidate QA pairs and a knowledge graph based on the context. The Reassembler utilizes the knowledge graph to get sequential QA pairs, and the Rewriter rewrites questions from a conversational perspective to obtain a multi-turn dataset S2M. Our experiments show that our method can synthesize effective training resources for CQA. Notably, S2M ranks 1st place on the QuAC leaderboard (https:\/\/quac.ai\/) at the time of submission (Aug 24th, 2022).<\/jats:p>","DOI":"10.3233\/faia230413","type":"book-chapter","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:12:18Z","timestamp":1695978738000},"source":"Crossref","is-referenced-by-count":2,"title":["S2M: Converting Single-Turn to Multi-Turn Datasets for Conversational Question Answering"],"prefix":"10.3233","author":[{"given":"Baokui","family":"Li","sequence":"first","affiliation":[{"name":"School of Software Technology, Zhejiang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sen","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software Technology, Zhejiang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wangshu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yicheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changlin","family":"Yang","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sen","family":"Hu","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Teng","family":"Xu","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siye","family":"Liu","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiwei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2023"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230413","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:12:20Z","timestamp":1695978740000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,28]]},"ISBN":["9781643684369","9781643684376"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230413","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,28]]}}}