3 citations · 6 across the 5 of their papers we have counts for
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cs.CL2020★ 1 cited
Distributional Discrepancy: A Metric for Unconditional Text Generation
Ping Cai, Xingyuan Chen, Peng Jin +2
The purpose of unconditional text generation is to train a model with real sentences, then generate novel sentences of the same quality and diversity as the training data. However,…
cs.CV2020★ 3 cited
Adding A Filter Based on The Discriminator to Improve Unconditional Text Generation
Xingyuan Chen, Ping Cai, Peng Jin +3
The autoregressive language model (ALM) trained with maximum likelihood estimation (MLE) is widely used in unconditional text generation. Due to exposure bias, the generated texts…