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What did you refer to? Evaluating Co-references in Dialogue

  • Westlake University
  • School of Computer Science and Technology
  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Existing neural end-to-end dialogue models have limitations on exactly interpreting the linguistic structures, such as ellipsis, anaphor and co-reference, etc., in dialogue history context. Therefore, it is hard to determine whether the dialogue models truly understand a dialogue or not, only depending on the coherence evaluation of their generated responses. To address these issues, in this paper, we proposed to directly measure the capability of dialogue models on understanding the entity-oriented structures via question answering and construct a new benchmark dataset, DEQA, including large-scale English and Chinese human-human dialogues. Experiments carried on representative dialogue models show that these models all face challenges on the proposed dialogue understanding task. The DEQA dataset will release for research use.

Original languageEnglish
Title of host publicationFindings of the Association for Computational Linguistics
Subtitle of host publicationACL-IJCNLP 2021
EditorsChengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
PublisherAssociation for Computational Linguistics (ACL)
Pages5075-5084
Number of pages10
ISBN (Electronic)9781954085541
DOIs
StatePublished - 2021
EventFindings of the Association for Computational Linguistics: ACL-IJCNLP 2021 - Virtual, Online
Duration: 1 Aug 20216 Aug 2021

Publication series

NameFindings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Conference

ConferenceFindings of the Association for Computational Linguistics: ACL-IJCNLP 2021
CityVirtual, Online
Period1/08/216/08/21

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