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MultiMDM achieves superior few-step generation by cleverly preserving the masking structure, enabling a drafting capability that enhances token refinement.
Deterministic policies can significantly enhance the stability and efficiency of reinforcement learning in complex mean field control problems, outperforming traditional stochastic approaches.
