{"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/when-and-why-are-pre-trained-word-embeddings","title":"When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?","arxiv_id":"1804.06323","date":"2018-04-17","proceeding":"NAACL 2018 6","authors":["Ye Qi","Devendra Singh Sachan","Matthieu Felix","Sarguna Janani Padmanabhan","Graham Neubig"],"abstract":"The performance of Neural Machine Translation (NMT) systems often suffers in\nlow-resource scenarios where sufficiently large-scale parallel corpora cannot\nbe obtained. Pre-trained word embeddings have proven to be invaluable for\nimproving performance in natural language analysis tasks, which often suffer\nfrom paucity of data. However, their utility for NMT has not been extensively\nexplored. In this work, we perform five sets of experiments that analyze when\nwe can expect pre-trained word embeddings to help in NMT tasks. We show that\nsuch embeddings can be surprisingly effective in some cases -- providing gains\nof up to 20 BLEU points in the most favorable setting.","url_abs":"http://arxiv.org/abs/1804.06323v2","url_pdf":"http://arxiv.org/pdf/1804.06323v2.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":"when-and-why-are-pre-trained-word-embeddings","repo_url":"https://github.com/neulab/word-embeddings-for-nmt","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"nmt","task_name":"NMT"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1804.06323","atlas_url":"https://app.syntology.ai/?focus=1804.06323","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}