{"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/self-regulation-employing-a-generative","title":"Self-regulation: Employing a Generative Adversarial Network to Improve Event Detection","arxiv_id":null,"date":"2018-07-01","proceeding":"ACL 2018 7","authors":["Yu Hong","Wenxuan Zhou","Jingli Zhang","Guodong Zhou","Qiaoming Zhu"],"abstract":"Due to the ability of encoding and mapping semantic information into a high-dimensional latent feature space, neural networks have been successfully used for detecting events to a certain extent. However, such a feature space can be easily contaminated by spurious features inherent in event detection. In this paper, we propose a self-regulated learning approach by utilizing a generative adversarial network to generate spurious features. On the basis, we employ a recurrent network to eliminate the fakes. Detailed experiments on the ACE 2005 and TAC-KBP 2015 corpora show that our proposed method is highly effective and adaptable.","url_abs":"https://aclanthology.org/P18-1048","url_pdf":"https://aclanthology.org/P18-1048.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":"self-regulation-employing-a-generative","repo_url":"https://github.com/JoeZhouWenxuan/Self-regulation-Employing-a-Generative-Adversarial-Network-to-Improve-Event-Detection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"event-detection","task_name":"Event Detection"},{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}