{"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/a-mixture-of-experts-model-for-antonym","title":"A Mixture-of-Experts Model for Antonym-Synonym Discrimination","arxiv_id":null,"date":"2021-08-01","proceeding":"ACL 2021 5","authors":["Zhipeng Xie","Nan Zeng"],"abstract":"Discrimination between antonyms and synonyms is an important and challenging NLP task. Antonyms and synonyms often share the same or similar contexts and thus are hard to make a distinction. This paper proposes two underlying hypotheses and employs the mixture-of-experts framework as a solution. It works on the basis of a divide-and-conquer strategy, where a number of localized experts focus on their own domains (or subspaces) to learn their specialties, and a gating mechanism determines the space partitioning and the expert mixture. Experimental results have shown that our method achieves the state-of-the-art performance on the task.","url_abs":"https://aclanthology.org/2021.acl-short.71","url_pdf":"https://aclanthology.org/2021.acl-short.71.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":"a-mixture-of-experts-model-for-antonym","repo_url":"https://github.com/zengnan1997/moe-asd","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"mixture-of-experts","task_name":"Mixture-of-Experts"}],"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}