Temporal‑Difference Objective Sharpenes Diffusion Models for Low‑Step Sampling
A new temporal‑difference objective forces diffusion models to stay consistent across denoising steps, boosting sample quality especially when only a few steps are used. The method treats denoising as policy evaluation in a Markov reward process and drops in as a plug‑in improvement for existing models.