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KAIST
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Unbalanced Wasserstein flow elegantly resolves finite-batch marginal fluctuations in generative models, unlocking significant unconditional generation gains on complex datasets.
NTRK achieves a 20脳 reduction in compute while surpassing the best baseline in aesthetic generation, revolutionizing reward-guided diffusion sampling.
