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Normalizing Flows can now compete with diffusion models on image generation tasks, thanks to an iterative denoising scheme that boosts performance without sacrificing likelihood-based training.
Forget generating entire videos – this method distills motion into a highly compressed latent space, letting you steer scene dynamics with text prompts at unprecedented speeds.
Tri-modal masked diffusion models can now be trained from scratch, achieving strong results in text generation, text-to-image, and text-to-speech, thanks to a systematic exploration of the design space and a novel SDE-based batch size reparameterization.
