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The method substantially improves upon previously reported FID scores for unguided generation and, notably, unconditional generation, where producing high-quality samples without guidance has been particularly challenging.
Equilibrium Forcing is introduced, a simplified framework for video denoising generative models without noise level conditioning that pioneers modular training- and inference-time designs for noise-unconditional generation that decouple learning the denoising field from sampling.
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