{"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/learning-crosslingual-word-embeddings-without","title":"Learning Crosslingual Word Embeddings without Bilingual Corpora","arxiv_id":"1606.09403","date":"2016-06-30","proceeding":"EMNLP 2016 11","authors":["Long Duong","Hiroshi Kanayama","Tengfei Ma","Steven Bird","Trevor Cohn"],"abstract":"Crosslingual word embeddings represent lexical items from different languages\nin the same vector space, enabling transfer of NLP tools. However, previous\nattempts had expensive resource requirements, difficulty incorporating\nmonolingual data or were unable to handle polysemy. We address these drawbacks\nin our method which takes advantage of a high coverage dictionary in an EM\nstyle training algorithm over monolingual corpora in two languages. Our model\nachieves state-of-the-art performance on bilingual lexicon induction task\nexceeding models using large bilingual corpora, and competitive results on the\nmonolingual word similarity and cross-lingual document classification task.","url_abs":"http://arxiv.org/abs/1606.09403v1","url_pdf":"http://arxiv.org/pdf/1606.09403v1.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":"learning-crosslingual-word-embeddings-without","repo_url":"https://github.com/longdt219/xlingualemb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"bilingual-lexicon-induction","task_name":"Bilingual Lexicon Induction"},{"task_slug":"cross-lingual-document-classification","task_name":"Cross-Lingual Document Classification"},{"task_slug":"document-classification","task_name":"Document Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"},{"task_slug":"word-similarity","task_name":"Word Similarity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.09403","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}