Huaiyi Dong

Action-Controlled Scale-Wise Flow Matching for Embodied World Models.

Experiments across action-conditioned robotic manipulation, visual planning, and model-based reinforcement learning, together with action-free driving video prediction, show that SAMPO++ improves visual prediction quality while providing stronger action alignment, counterfactual accuracy, no-op residual suppression, and long-horizon rollout consistency over strong discrete and continuous baselines.