MLLM Security

Multimodal large language model (MLLM) security research focuses on mitigating the risks associated with these powerful AI systems, which combine language processing with image and other modalities. Current efforts concentrate on developing robust evaluation suites to assess safety across multiple dimensions (e.g., bias, toxicity, privacy), improving instruction tuning methods to enhance model control and reduce harmful outputs, and designing defense mechanisms to protect against malicious inputs, particularly images. This field is crucial for ensuring the responsible deployment of MLLMs in various applications, preventing unintended harm, and advancing the trustworthiness of AI.