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Individual token selection and metadata caching unlock sparse attention for diffusion transformers without sacrificing generation quality, achieving up to $2.32\times$ speedups.
High-fidelity 3D texture generation is now achievable without any 3D assets, by cleverly transforming 2D images into effective training data.
