Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using textdescriptions orreference images, while preserving irrelevant attributes(e.g.,identity,background,cloth).

Diffusion models (DMs) have been significantly developed and widely used in various applications due to their excellent generative qualities.

We derive a tighter inequality than Cauchy-Schwarz Inequality, leverage it to refine Pearson's

Machine unlearning (MU) empowers individuals with the'right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains uncertain whether MU can be effectively applied to Multimodal Large Language Models (MLLMs), particularly in scenarios of forgetting the leaked visual data of concepts.

Neural circuits are typically comprised of populations of primary (excitatory) neurons and local (inhibitory) interneurons.