3 accepted papers
Multimodal Large Language Models (MLLMs) contain a substantial amount of factual knowledge, which may become outdated or inaccurate over time. Consequently, various knowledge editing techniques have been proposed to update the knowledge encoded within these models. Previous approaches maintain modal…
Backdoor attacks remain significant security threats to generative large language models (LLMs). Since generative LLMs output sequences of high-dimensional token logits instead of low-dimensional classification logits, most existing backdoor defense methods designed for discriminative models like BE…
Multimodal sentiment analysis aims to utilize different modalities including language, visual, and audio to identify human emotions in videos. Multimodal interaciton mechanism is the key challenge. Previous works lack modeling of multimodal interaction at different grain levels, and does not suppres…