{"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/multi-task-learning-for-argumentation-mining","title":"Multi-Task Learning for Argumentation Mining in Low-Resource Settings","arxiv_id":"1804.04083","date":"2018-04-11","proceeding":"NAACL 2018 6","authors":["Claudia Schulz","Steffen Eger","Johannes Daxenberger","Tobias Kahse","Iryna Gurevych"],"abstract":"We investigate whether and where multi-task learning (MTL) can improve\nperformance on NLP problems related to argumentation mining (AM), in particular\nargument component identification. Our results show that MTL performs\nparticularly well (and better than single-task learning) when little training\ndata is available for the main task, a common scenario in AM. Our findings\nchallenge previous assumptions that conceptualizations across AM datasets are\ndivergent and that MTL is difficult for semantic or higher-level tasks.","url_abs":"http://arxiv.org/abs/1804.04083v3","url_pdf":"http://arxiv.org/pdf/1804.04083v3.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":"multi-task-learning-for-argumentation-mining","repo_url":"https://github.com/UKPLab/naacl18-multitask_argument_mining","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"}],"methods":[{"method_slug":"am","method_name":"AM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.04083","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}