Broken Memories: Detecting and Mitigating Memorization

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations

arXiv:2605.22050v4 Announce Type: replace Abstract: While diffusion models excel at generating high-quality images, their tendency to memorize training data poses significant privacy and copyright risks. In this work, we for the first time identify that memorization induces internal numerical instability, often manifesting as visually ``broken'' artifacts. Inspired by stability analysis in numerical methods, we introduce empirical stability regions based on latent update norms to...