Papers with representation capacity

1 papers
Controlled Text Generation Using Dictionary Prior in Variational Autoencoders (2022.findings-acl)

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Challenge: Variational autoencoders (VAEs) have been widely applied in text generation tasks, but they suffer from insufficient representation capacity and poor controllability.
Approach: They propose a data-driven prior that has expressivity and controllability.
Outcome: The proposed prior enjoys expressivity and controllability and can be used in language modeling and controlled text generation.

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