Pruning for Robust Concept Erasing in Diffusion Models

Understand

Despite the impressive capabilities of generating images, text-to-image diffusion models are susceptible to producing undesirable outputs such as NSFW content and copyrighted artworks.

• To address this issue, recent studies have focused on fine-tuning model parameters to erase problematic concepts.
• However, existing methods exhibit a major flaw in robustness, as fine-tuned models often reproduce the undesirable outputs when faced with cleverly crafted prompts.
• This reveals a fundamental limitation in the current approaches and may raise risks for the deployment of diffusion models in the open world.