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A Semi-Supervised Stable Variational Network for Promoting Replier-Consistency in Dialogue Generation (D19-1)

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Challenge: Existing methods favor uninformative and non replier-specific responses due to lack of relevant information guidance.
Approach: They propose to use a semi-supervised variable network to generate replier-specific responses . they use vMF as latent space to obtain stable KL performance .
Outcome: The proposed model outperforms baseline models on two large conversation datasets and generates diverse and replier-specific responses.

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