{"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/addressing-the-rare-word-problem-in-neural","title":"Addressing the Rare Word Problem in Neural Machine Translation","arxiv_id":"1410.8206","date":"2014-10-30","proceeding":"IJCNLP 2015 7","authors":["Minh-Thang Luong","Ilya Sutskever","Quoc V. Le","Oriol Vinyals","Wojciech Zaremba"],"abstract":"Neural Machine Translation (NMT) is a new approach to machine translation\nthat has shown promising results that are comparable to traditional approaches.\nA significant weakness in conventional NMT systems is their inability to\ncorrectly translate very rare words: end-to-end NMTs tend to have relatively\nsmall vocabularies with a single unk symbol that represents every possible\nout-of-vocabulary (OOV) word. In this paper, we propose and implement an\neffective technique to address this problem. We train an NMT system on data\nthat is augmented by the output of a word alignment algorithm, allowing the NMT\nsystem to emit, for each OOV word in the target sentence, the position of its\ncorresponding word in the source sentence. This information is later utilized\nin a post-processing step that translates every OOV word using a dictionary.\nOur experiments on the WMT14 English to French translation task show that this\nmethod provides a substantial improvement of up to 2.8 BLEU points over an\nequivalent NMT system that does not use this technique. With 37.5 BLEU points,\nour NMT system is the first to surpass the best result achieved on a WMT14\ncontest task.","url_abs":"http://arxiv.org/abs/1410.8206v4","url_pdf":"http://arxiv.org/pdf/1410.8206v4.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":"addressing-the-rare-word-problem-in-neural","repo_url":"https://github.com/atpaino/deep-text-corrector","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"addressing-the-rare-word-problem-in-neural","repo_url":"https://github.com/gongshuangshuang/deep-text-corrector","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"addressing-the-rare-word-problem-in-neural","repo_url":"https://github.com/sambit9238/deep_text_corrector","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"addressing-the-rare-word-problem-in-neural","repo_url":"https://github.com/sunnysinghnitb/text-corrector-software","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"addressing-the-rare-word-problem-in-neural","repo_url":"https://github.com/sunnysinghnitb/text_corrector_software","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"nmt","task_name":"NMT"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"word-alignment","task_name":"Word Alignment"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/machine-translation-on-wmt2014-english-french","task":"Machine Translation","dataset":"WMT2014 English-French","model":"LSTM6 + PosUnk","rank_in_archive_order":41,"of":57,"metrics":{"BLEU score":"37.5"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1410.8206","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}