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Autoregressive video generation gets a 6x speed boost without sacrificing quality, thanks to a motion-aware caching strategy that finally respects the fact that not all pixels are created equal.
Achieve significant speedups in diffusion model inference, without training, by adaptively selecting the best predictor for each token at each step based on a low-cost probe of the first layer.
Autoregressive video models can now generate 4-minute videos without retraining, thanks to a clever inference-time hack that fixes positional embedding bias and injects dynamic priors.
