3 papers
cs.AI2026
Towards Benign Memory Forgetting for Selective Multimodal Large Language Model Unlearning
Zhen Zeng, Leijiang Gu, Zhangling Duan +4
Multimodal large language models (MLLMs) can inadvertently memorize privacy-sensitive information during training. While existing unlearning methods can remove such content, they o…
cs.CL2026
Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models
Leijiang Gu, Zhen Zeng, Feng Li +2
Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Language Models (MLLMs). However, t…
cs.AI2026
CrossCult-KIBench: A Benchmark for Cross-Cultural Knowledge Insertion in MLLMs
Zhen Zeng, Leijiang Gu, Feng Li +2
Multimodal Large Language Models (MLLMs), trained primarily on English-centric data, frequently generate culturally inappropriate or misaligned responses in cross-cultural settings…