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AnyStep-WAM introduces a framework for tunable-budget prediction and adaptive inference in world-action models, reducing denoising steps by significant margins while maintaining task success rates in robotic manipulation.
The paper proposes a training-free decoding method called Refusal-Aware Early Commitment (RAEC) to improve safety alignment in diffusion language models by leveraging refusal signals from early denoising steps.