Review for NeurIPS paper: TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation

In equation (11), will the importance sampling of y also cause high-variance during the estimation? Is this also affected by the accuracy of neighborhood distribution (joint distribution) in equation 13? If yes, what's the performance if you use other types of kernel functions? Why don't use pre-trained language models to evaluate the PPL? e.g., GPT-2 Other comments: 1. It is helpful to elaborate more or mention the joint distribution will be introduced in 3.1.2,