4 papers
DREAM: Dynamic Red-teaming across Environments for AI Models
Liming Lu, Xiang Gu, Junyu Huang +5
Large Language Models (LLMs) are increasingly used in agentic systems, where their interactions with diverse tools and environments create complex, multi-stage safety challenges. H…
Multimodal Robust Prompt Distillation for 3D Point Cloud Models
Xiang Gu, Liming Lu, Xu Zheng +3
Adversarial attacks pose a significant threat to learning-based 3D point cloud models, critically undermining their reliability in security-sensitive applications. Existing defense…
CIARD: Cyclic Iterative Adversarial Robustness Distillation
Liming Lu, Shuchao Pang, Xu Zheng +4
Adversarial robustness distillation (ARD) aims to transfer both performance and robustness from teacher model to lightweight student model, enabling resilient performance on resour…
EAT: Multimodal Jailbreak Defense via Dynamic Joint Optimization for Multimodal Large Language Models
Liming Lu, Xiang Gu, Shuchao Pang +5
Research endeavors have been made in learning robust Multimodal Large Language Models (MLLMs) against jailbreak attacks. However, existing methods for improving MLLMs' robustness s…