Rui Pan

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance

2024 · arXiv (Cornell University)

The deployment of multimodal large language models (MLLMs) has brought forth a unique vulnerability: susceptibility to malicious attacks through visual inputs. This paper investigates the novel challenge of defending MLLMs against such attacks. Compared to …