Unifying Distributional Training for One-Step Visual Generation
A unified theoretical framework is introduced that separates distribution modeling from matching discrepancy and connects global objectives to pointwise feature updates through Wasserstein gradient flow and motivates MGFlow, which models feature distributions with Gaussian mixtures at an adjustable granularity between...
Chi Zhang, Hao-Yan Shi, Yue-Yi Liu et al.
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