Derives closed-form optimal coefficient for conditional velocity as control variate in MeanFlow loss, unifying remedies and revealing mismatch between gradient-MSE and FID optima.
Simplifying, stabilizing and scaling continuous-time consistency models
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JFDL allows pre-trained Consistency Models to perform guided image generation post-hoc by aligning flow distributions, reducing FID scores on CIFAR-10 and ImageNet without needing a teacher model.
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On Variance Reduction in Learning Mean Flows
Derives closed-form optimal coefficient for conditional velocity as control variate in MeanFlow loss, unifying remedies and revealing mismatch between gradient-MSE and FID optima.