Andrea Tonello

A Unified Framework for Diffusion Model Unlearning with f-Divergence

Most current methods for unlearning concepts in text-to-image diffusion models rely on mean squared error-based loss functions to align target distributions with anchors. In this paper, we generalize this idea into a unified $f$-divergence-based framework that recovers the standard mean squared erro…