arXiv Computation and Language August 31, 2026 By Wonjun Lee, Jaehyuk Jang, Kangwook Ko, Hee-Seon Kim, Changick Kim

AIM: Anchor Identity Features, Then Match for Multimodal Large Language Model Unlearning

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The paper introduces AIM, a two‑stage approach for unlearning identity‑specific information from multimodal large language models (MLLMs) when retain images are not available at deletion time. AIM first anchors an identity‑forgetting target using a universal visual prompt, then aligns the vision encoder to this target under a Fisher‑based constraint. Experiments demonstrate that AIM effectively removes identity knowledge while preserving other visual perception capabilities and prior knowledge.

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