Papers by Mingyue Han

2 papers
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models (2021.acl-short)

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Challenge: Pretrained language models (PLMs) achieve surprising performance on the Choice of Plausible Alternatives (COPA) task.
Approach: They propose to add a regularization loss to the existing COPA models to mitigate the problem of semantic similarity bias by adding a normalization loss.
Outcome: The proposed model improves generalization ability and performs better on a challenging dataset, BCOPA-CE, which has unbiased token distribution and is more difficult for models to distinguish cause and effect.
Entity Resolution in Open-domain Conversations (2021.naacl-industry)

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Challenge: Recent work on incorporating external knowledge into the response generation models has attracted great interest.
Approach: They propose a neural entity linking approach to incorporate external knowledge into the response generation models to improve the relevancy of retrieved knowledge.
Outcome: The proposed approach outperforms the baseline model by 62.8% relative to the baseline.

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