4 papers
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Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Language Models (MLLMs).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…
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…
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…
Visual-Oriented Fine-Grained Knowledge Editing for MultiModal Large Language Models
Zhen Zeng, Leijiang Gu, Xun Yang +3
Knowledge editing aims to efficiently and cost-effectively correct inaccuracies and update outdated information. Recently, there has been growing interest in extending knowledge ed…