{"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/bilingual-learning-of-multi-sense-embeddings","title":"Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders","arxiv_id":"1603.09128","date":"2016-03-30","proceeding":"NAACL 2016 6","authors":["Simon Šuster","Ivan Titov","Gertjan van Noord"],"abstract":"We present an approach to learning multi-sense word embeddings relying both\non monolingual and bilingual information. Our model consists of an encoder,\nwhich uses monolingual and bilingual context (i.e. a parallel sentence) to\nchoose a sense for a given word, and a decoder which predicts context words\nbased on the chosen sense. The two components are estimated jointly. We observe\nthat the word representations induced from bilingual data outperform the\nmonolingual counterparts across a range of evaluation tasks, even though\ncrosslingual information is not available at test time.","url_abs":"http://arxiv.org/abs/1603.09128v1","url_pdf":"http://arxiv.org/pdf/1603.09128v1.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":"bilingual-learning-of-multi-sense-embeddings","repo_url":"https://github.com/rug-compling/bimu","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}