Large-scale neural networks have revolutionized generative models by granting them an unprecedented ability to capture complex relationships among varies variables. Among this model family, diffusion models stand out as a power approach for image generation. Nevertheless, when dealing with discrete data, diffusion models still fall short of the performance achieved by autoregressive models. Alex Graves, a renowned researcher in the field of machine learnin