AINeutralarXiv – CS AI · May 96/10
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Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning
Researchers present a novel machine unlearning approach for Multimodal Large Language Models that selectively removes target visual knowledge while preserving non-target information across both visual and textual modalities. The method uses contrastive visual forgetting and null space constraints to balance effective forgetting with knowledge retention, extending applicability to continual unlearning scenarios.