{"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/joint-learning-of-pre-trained-and-random","title":"Joint Learning of Pre-Trained and Random Units for Domain Adaptation in Part-of-Speech Tagging","arxiv_id":"1904.03595","date":"2019-04-07","proceeding":"NAACL 2019 6","authors":["Sara Meftah","Youssef Tamaazousti","Nasredine Semmar","Hassane Essafi","Fatiha Sadat"],"abstract":"Fine-tuning neural networks is widely used to transfer valuable knowledge\nfrom high-resource to low-resource domains. In a standard fine-tuning scheme,\nsource and target problems are trained using the same architecture. Although\ncapable of adapting to new domains, pre-trained units struggle with learning\nuncommon target-specific patterns. In this paper, we propose to augment the\ntarget-network with normalised, weighted and randomly initialised units that\nbeget a better adaptation while maintaining the valuable source knowledge. Our\nexperiments on POS tagging of social media texts (Tweets domain) demonstrate\nthat our method achieves state-of-the-art performances on 3 commonly used\ndatasets.","url_abs":"http://arxiv.org/abs/1904.03595v1","url_pdf":"http://arxiv.org/pdf/1904.03595v1.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":[],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"pos","task_name":"POS"},{"task_slug":"pos-tagging","task_name":"POS Tagging"},{"task_slug":"part-of-speech-tagging","task_name":"Part-Of-Speech Tagging"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/part-of-speech-tagging-on-social-media","task":"Part-Of-Speech Tagging","dataset":"Social media","model":"PretRand","rank_in_archive_order":1,"of":3,"metrics":{"Accuracy":"91.46"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}