Eval all, trust a few, do wrong to none: Comparing sentence generation models

21 Apr 2018Ondřej CífkaAliaksei SeverynEnrique AlfonsecaKatja Filippova

In this paper, we study recent neural generative models for text generation related to variational autoencoders. Previous works have employed various techniques to control the prior distribution of the latent codes in these models, which is important for sampling performance, but little attention has been paid to reconstruction error... (read more)

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