{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T23:35:29Z","timestamp":1762040129234,"version":"build-2065373602"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Paraphrase generation plays key roles in NLP tasks such as question answering, machine translation, and information retrieval. In this paper, we propose a novel framework for paraphrase generation. It simultaneously decodes the output sentence using a pretrained wordset-to-sequence model and a round-trip translation model. We evaluate this framework on Quora, WikiAnswers, MSCOCO and Twitter, and show its advantage over previous state-of-the-art unsupervised methods and distantly-supervised methods by significant margins on all datasets. For Quora and WikiAnswers, our framework even performs better than some strongly supervised methods with domain adaptation. Further, we show that the generated paraphrases can be used to augment the training data for machine translation to achieve substantial improvements.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/525","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"3815-3821","source":"Crossref","is-referenced-by-count":6,"title":["Automatically Paraphrasing via Sentence Reconstruction and  Round-trip Translation"],"prefix":"10.24963","author":[{"given":"Zilu","family":"Guo","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongqiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Alibaba Damo Academy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenny Q.","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guandan","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Damo Academy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaibo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Alibaba Damo Academy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boxing","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Damo Academy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Huang","sequence":"additional","affiliation":[{"name":"Alibaba Damo Academy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:03:52Z","timestamp":1628679832000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/525"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/525","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}