Collaborative Training of GANs in Continuous and Discrete Spaces for Text Generation

Yanghoon Kim
Yanghoon Kim
Seungpil Won
Seungpil Won

IEEE Access, pp. 226515-226523, 2020.

Cited by: 0|Bibtex|Views4|DOI:https://doi.org/10.1109/ACCESS.2020.3045166
Other Links: arxiv.org|academic.microsoft.com

Abstract:

Applying generative adversarial networks (GANs) to text-related tasks is challenging due to the discrete nature of language. One line of research resolves this issue by employing reinforcement learning (RL) and optimizing the next-word sampling policy directly in a discrete action space. Such methods compute the rewards from complete se...More

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