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MultiMDM achieves superior few-step generation by cleverly preserving the masking structure, enabling a drafting capability that enhances token refinement.
KL-regularization in multi-armed bandits provably achieves near-optimal regret, scaling linearly with the number of arms, a significant improvement over classical results.
