subspace-learning

This paper introduces ASAM (Adversarial Subspace Alignment for Multimodal Knowledge Editing), a method that improves the generality of intrinsic multimodal knowledge editing by generating adversarial yet semantically coherent variants and enforcing low-rank alignment of representations, addressing the limited generalization of existing methods.