Orthogonal Concept Erasure for Diffusion Models

This research paper investigates the limitations of current concept erasure methods for mitigating undesired content in diffusion models. It identifies that additive parameter updates in editing-based methods cause entanglement between concept semantics and overall generative capacity, proposing a new solution to enhance precision and preservation.