Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation

ACL 2020 Arya D. McCarthyXian LiJiatao GuNing Dong

This paper proposes a simple and effective approach to address the problem of posterior collapse in conditional variational autoencoders (CVAEs). It thus improves performance of machine translation models that use noisy or monolingual data, as well as in conventional settings... (read more)

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