Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning

ArXi:2606.00105v1 Announce Type: cross Multimodal Large Language Models (MLLMs) have achieved remarkable progress on vision-language tasks, but they may also memorize and expose sensitive or restricted knowledge, raising concerns about privacy and broader safety risks. Machine Unlearning (MU) provides a promising way to remove targeted undesirable knowledge from trained models without re