r/MachineLearning - [D] [R] Any new tricks for training GANs on discrete data?

The original GAN paper by Goodfellow et al did not work for discrete data because of the inability to the backproagate gradient to the generator. Have there been any recent developments in this directions since, allowing the adversarial idea to be implemented for discrete data? And still take advantage of the automatic differentiation (backpropagation) facilities of libraries like PyTorch / Tensorflow?