{"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/identifying-semantic-divergences-in-parallel","title":"Identifying Semantic Divergences in Parallel Text without Annotations","arxiv_id":"1803.11112","date":"2018-03-29","proceeding":"NAACL 2018 6","authors":["Yogarshi Vyas","Xing Niu","Marine Carpuat"],"abstract":"Recognizing that even correct translations are not always semantically\nequivalent, we automatically detect meaning divergences in parallel sentence\npairs with a deep neural model of bilingual semantic similarity which can be\ntrained for any parallel corpus without any manual annotation. We show that our\nsemantic model detects divergences more accurately than models based on surface\nfeatures derived from word alignments, and that these divergences matter for\nneural machine translation.","url_abs":"http://arxiv.org/abs/1803.11112v1","url_pdf":"http://arxiv.org/pdf/1803.11112v1.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":"identifying-semantic-divergences-in-parallel","repo_url":"https://github.com/yogarshi/SemDiverge","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"semantic-similarity","task_name":"Semantic Similarity"},{"task_slug":"semantic-textual-similarity","task_name":"Semantic Textual Similarity"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.11112","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}