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Achieving seamless audio-visual identity swapping in talking videos while preserving original dynamics could revolutionize content creation and personalization.
Naive matching in diffusion distillation can inadvertently amplify errors due to hidden information in teacher models, leading to a surprising failure mode called Negative Branch Asymmetry.
