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SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching

1 reports1 reporting sourcesUpdated 2 days ago

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SpectralCache is a training-free framework that accelerates diffusion-based world models by leveraging stable singular subspaces and predictable singular value evolution, achieving 5.22x speedup with minimal quality loss in static scenes.

Generated from attributed reports · Updated 2 hours ago

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10/9
  1. arXiv Robotics — research abstracts
    SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching

    This research proposes SpectralCache, a training-free spectral caching framework for diffusion-based world models. By exploiting the stable singular subspaces and predictable evolution of singular values across denoising steps, SpectralCache improves inference efficiency while preserving generation quality. Experiments show 5.22x acceleration on HunyuanWorld-Voyager-13B with a WorldScore of 65.90 for static scenes.

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