Combining Diffusion Models and Autoregression: this project aims to unify the strengths of Autoregressive (AR) and diffusion models, leveraging AR’s sequential factorization for language modeling and diffusion’s iterative refinement for visual generation. The goal is to create a flexible framework that integrates both paradigms for improved generative performance across domains.