DiFA: Inference-Time Forward-Process Alignment for Diffusion Models
This paper proposes a new way to improve the performance of diffusion models by aligning their inference process with the forward statistical structure of the model. This can lead to more realistic and diverse generated images, which is important for applications like image generation.