NeurIPS 2020

TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation

Meta Review

This paper proposed a novel method for GAN-based natural language generation, where first order Taylor expension is used to estimate the gradient of the reword function. This method greatly mitigate the high variance problem of previous methods and improve the sample efficiency. Experiments show the proposed method achieve the state-of-the-art. The work is solid both in theory and in experiments.