Papers with Multi-Turn dialogue Reasoning

1 papers
MuTual: A Dataset for Multi-Turn Dialogue Reasoning (2020.acl-main)

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Challenge: Existing non-task oriented dialogue systems can yield a relevant and fluent response, but sometimes make logical mistakes because of weak reasoning capabilities.
Approach: They propose a dataset for multi-turn dialogue reasoning that uses annotated dialogues to train a machine to handle various reasoning problems.
Outcome: Empirical results show that state-of-the-art methods only reach 71%, far behind human performance of 94%.

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