DADiff: Diffusion Models Bridge the Dynamics Gap in Cross-Domain RL Policy Transfer

arXiv·medium signal

Hanyang Chen, Anirudh Satheesh and Longchao Da (arXiv 2607.16090, cs.LG/cs.AI) use a diffusion model to adapt policies across domains whose dynamics don't match — the standard sim-to-real failure where a policy trained in one environment degrades in another. Rather than retraining, DADiff learns the transformation between domain dynamics. The practical read: diffusion is increasingly being used as a general-purpose distribution-bridging tool, not just a generative one.