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#

diffusionmodel

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This paper presents β-CFG, a dynamic guidance method for text-to-image diffusion models. Unlike standard CFG, which uses a fixed guidance scale, β-CFG adapts guidance strength over time using a β-distribution. This improves image quality, keeps sampling closer to the data manifold, and achieves better FID while maintaining prompt alignment.

  • Updated Mar 2, 2025
  • Python

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