{"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/effects-of-pre-and-post-processing-on-type","title":"Effects of Pre- and Post-Processing on type-based Embeddings in Lexical Semantic Change Detection","arxiv_id":"2101.09368","date":"2021-01-22","proceeding":"EACL 2021 2","authors":["Jens Kaiser","Sinan Kurtyigit","Serge Kotchourko","Dominik Schlechtweg"],"abstract":"Lexical semantic change detection is a new and innovative research field. The optimal fine-tuning of models including pre- and post-processing is largely unclear. We optimize existing models by (i) pre-training on large corpora and refining on diachronic target corpora tackling the notorious small data problem, and (ii) applying post-processing transformations that have been shown to improve performance on synchronic tasks. Our results provide a guide for the application and optimization of lexical semantic change detection models across various learning scenarios.","url_abs":"https://arxiv.org/abs/2101.09368v2","url_pdf":"https://arxiv.org/pdf/2101.09368v2.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":"effects-of-pre-and-post-processing-on-type","repo_url":"https://github.com/Garrafao/LSCDetection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"change-detection","task_name":"Change Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2101.09368","atlas_url":"https://app.syntology.ai/?focus=2101.09368","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}