Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models
This work proposes Causal Localization and Retain-Aware Projection (CLRP), a lightweight training-free framework that uses activation patching to identify the layer that causally mediates target-attribute disclosure, then applies a retain-aware projection that removes the target-attribute subspace while preserving same-identity evidence.