3 citations · 6 across the 5 of their papers we have counts for
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cs.CV2019
The Detection of Distributional Discrepancy for Text Generation
Xingyuan Chen, Ping Cai, Peng Jin +4
The text generated by neural language models is not as good as the real text. This means that their distributions are different. Generative Adversarial Nets (GAN) are used to allev…
cs.LG2019★ 2 cited
Adversarial Sub-sequence for Text Generation
Xingyuan Chen, Yanzhe Li, Peng Jin +4
Generative adversarial nets (GAN) has been successfully introduced for generating text to alleviate the exposure bias. However, discriminators in these models only evaluate the ent…