2026
DeRaDiff: Denoising Time Realignment of Diffusion Models
ICLR 2026poster
Recent advances align diffusion models with human preferences to increase aesthetic appeal and mitigate artifacts and biases. Such methods aim to maximize a conditional output distribution aligned with higher rewards whilst not drifting far from a pretrained prior. This is commonly enforced by KL (K…