{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T19:52:45Z","timestamp":1759693965873},"reference-count":3,"publisher":"MIT Press - Journals","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["TACL"],"published-print":{"date-parts":[[2014,12]]},"abstract":"<jats:p> We present MultiP (Multi-instance Learning Paraphrase Model), a new model suited to identify paraphrases within the short messages on Twitter. We jointly model paraphrase relations between word and sentence pairs and assume only sentence-level annotations during learning. Using this principled latent variable model alone, we achieve the performance competitive with a state-of-the-art method which combines a latent space model with a feature-based supervised classifier. Our model also captures lexically divergent paraphrases that differ from yet complement previous methods; combining our model with previous work significantly outperforms the state-of-the-art. In addition, we present a novel annotation methodology that has allowed us to crowdsource a paraphrase corpus from Twitter. We make this new dataset available to the research community. <\/jats:p>","DOI":"10.1162\/tacl_a_00194","type":"journal-article","created":{"date-parts":[[2018,12,28]],"date-time":"2018-12-28T15:43:26Z","timestamp":1546011806000},"page":"435-448","source":"Crossref","is-referenced-by-count":31,"title":["Extracting Lexically Divergent Paraphrases from                     Twitter"],"prefix":"10.1162","volume":"2","author":[{"given":"Wei","family":"Xu","sequence":"first","affiliation":[{"name":"University of Pennsylvania, Philadelphia, PA, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan","family":"Ritter","sequence":"additional","affiliation":[{"name":"The Ohio State University, Columbus, OH, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chris","family":"Callison-Burch","sequence":"additional","affiliation":[{"name":"University of Pennsylvania, Philadelphia, PA, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William B.","family":"Dolan","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangfeng","family":"Ji","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"p_2","author":"Androutsopoulos I.","year":"2010","journal-title":"Journal of Artificial Intelligence Research, 38."},{"key":"p_5","author":"Burrows S.","year":"2012","journal-title":"Transactions on Intelligent Systems and Technology (ACM TIST)."},{"key":"p_40","author":"Ritter A.","year":"2013","journal-title":"Transactions of the Association for Computational Linguistics (TACL)."}],"container-title":["Transactions of the Association for Computational Linguistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/tacl_a_00194","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:38:59Z","timestamp":1615585139000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/tacl\/article\/43332"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12]]},"references-count":3,"alternative-id":["10.1162\/tacl_a_00194"],"URL":"https:\/\/doi.org\/10.1162\/tacl_a_00194","relation":{},"ISSN":["2307-387X"],"issn-type":[{"value":"2307-387X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12]]}}}