Papers by Yugui Han

    1 papers
    TransS-Driven Joint Learning Architecture for Implicit Discourse Relation Recognition (2020.acl-main)

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    Challenge: Existing approaches to implicit discourse relation recognition lack connectives as strong linguistic clues.
    Approach: They propose a transS-driven joint learning architecture to translate discourse relations in low-dimensional embedding space and exploit the semantic features of arguments to assist discourse understanding.
    Outcome: The proposed model outperforms existing systems on the Penn Discourse TreeBank.

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