Latent Code and Text-based Generative Adversarial Networks for Soft-text Generation

NAACL 2019 Md. Akmal HaidarMehdi RezagholizadehAlan Do-OmriAhmad Rashid

Text generation with generative adversarial networks (GANs) can be divided into the text-based and code-based categories according to the type of signals used for discrimination. In this work, we introduce a novel text-based approach called Soft-GAN to effectively exploit GAN setup for text generation... (read more)

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