SPE-74.4
End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline
Tuan Lai, University of Illinois at Urbana-Champaign, United States of America; Trung Bui, Adobe, United States of America; Doo-Soon Kim, Roku, Inc., United States of America
Session:
Representations and Relationships in Language
Track:
Speech and Language Processing
Location:
Gather Area E
Presentation Time:
Thu, 12 May, 22:00 - 22:45 China Time (UTC +8)
Thu, 12 May, 14:00 - 14:45 UTC
Thu, 12 May, 14:00 - 14:45 UTC
Session Co-Chairs:
Sibel Oyman, Apple and Malu Zhang, University of Electronic Science and Technology of China
Session SPE-74
SPE-74.1: INTEGRATING DEPENDENCY TREE INTO SELF-ATTENTION FOR SENTENCE REPRESENTATION
Junhua Ma, Yuxuan Liu, Shangbo Zhou, Chongqing University, China; Jiajun Li, Xue Li, The University of Queensland, Australia
SPE-74.2: MetricBERT: Text Representation Learning via Self-Supervised Triplet Training
Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Yoni Weill, Noam Koenigstein, microsoft, Israel
SPE-74.4: End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline
Tuan Lai, University of Illinois at Urbana-Champaign, United States of America; Trung Bui, Adobe, United States of America; Doo-Soon Kim, Roku, Inc., United States of America
SPE-74.5: LOCAL CONTEXT INTERACTION-AWARE GLYPH-VECTORS FOR CHINESE SEQUENCE TAGGING
JunYu Lu, PingJian Zhang, South China University of Technology, China