[R] CFG++ : A simple fix for addressing the flaws of CFG in diffusion models

The classifier-free guidance (CFG) is widely used for text-guidance in diffusion models, but notorious for its challenges, such as difficulty in DDIM inversion and ambiguity in selecting a large guidance scale.

This paper demonstrates that these limitations of CFG stem from inherent design flaws in the original CFG, and introduce CFG++, a simple yet powerful fix in the \**re\**nosing process. This adjustment facilitates smaller guidance scales, significantly improved invertibility, and much better alignment between images and text.

Project page: [https://cfgpp-diffusion.github.io/](https://cfgpp-diffusion.github.io/) …

challenges classifier design diffusion diffusion models fix flaws free guidance limitations machinelearning paper scale simple stem text