Papers by Zhufeng Pan

2 papers
Improving Open-Domain Dialogue Systems via Multi-Turn Incomplete Utterance Restoration (D19-1)

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Challenge: Experimental results show that restoring incomplete utterances from context improves the performance of open-domain dialogue systems.
Approach: They propose to use a dataset to restore incomplete utterances from context . they propose to pick and combine the data to restore the incomplete .
Outcome: The proposed model significantly boosts response quality of open-domain dialogue systems.
Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text (2021.findings-acl)

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Challenge: Existing methods for sentiment analysis do not consider direction of sentiments between political entities.
Approach: They propose a novel task of identifying directed sentiment relationship between political entities from a given news document.
Outcome: The proposed method is useful for social science research questions in the 2016 election and COVID-19.

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