Rethinking supervision targets for multimodal LLM unlearning: less private information, reduced distribution shift
Read the original at arxiv.org→arXiv:2611.09939v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) can memorize and reproduce sensitive information from their training data, posing significant privacy risks. Their ability to...
Original headline: "Rethinking Supervision Targets for Multimodal LLM Unlearning: Less Private Information, Reduced Distribution Shift"
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- Nov 10, 05:00 UTC arXiv cs.CL lead source Rethinking Supervision Targets for Multimodal LLM Unlearning: Less Private Information, Reduced Distribution Shift