BEGIN:VCALENDAR BEGIN:VEVENT SUMMARY:PhD Thesis Proposal - Wenzuan Zhou DESCRIPTION:PhD Candidate: Wenxuan Zhou\n \n Title: Relation Extraction: Models, Robustness, and Generalization\n \n Chair: Muhao Chen\n Committee members: Laurent Itti, Jonathan May, Tianshu Sun, Robin Jia\n \n \n Abstract: With large amounts of digital text generated every day, it is important to extract structured knowledge automatically from the text. Relation extraction (RE), as one essential step of the solution, aims at identifying relationships among entities in a given piece of text. In this thesis proposal, I will present my work during my Ph.D. on RE from three perspectives: (1) designing effective RE models based on pretrained language models; (2) Improving the robustness of RE models, especially against entity bias; and (3) building data-efficient RE models in low-resource scenarios, which is important for real-world applications. After these, I will introduce my ongoing work and future directions for RE.\n \n \n DTSTART:20221213T090000 LOCATION: URL;VALUE=URI: DTEND:20221213T230000 END:VEVENT END:VCALENDAR