4 papers
MemEvoBench: Benchmarking Safety Risks from Memory Misevolution in LLM Agents
Weiwei Xie, Shaoxiong Guo, Fan Zhang +5
Equipping Large Language Models (LLMs) with persistent memory enhances interaction continuity and personalization but introduces new safety risks. Specifically, contaminated or bia…
DeepSight: An All-in-One LM Safety Toolkit
Bo Zhang, Jiaxuan Guo, Lijun Li +17
As the development of Large Models (LMs) progresses rapidly, their safety is also a priority. In current Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) s…
STaR-Attack: A Spatio-Temporal and Narrative Reasoning Attack Framework for Unified Multimodal Understanding and Generation Models
Shaoxiong Guo, Tianyi Du, Lijun Li +3
Unified Multimodal understanding and generation Models (UMMs) have demonstrated remarkable capabilities in both understanding and generation tasks. However, we identify a vulnerabi…
VGA: Vision GUI Assistant -- Minimizing Hallucinations through Image-Centric Fine-Tuning
Ziyang Meng, Yu Dai, Zezheng Gong +3
Recent advances in Large Vision-Language Models (LVLMs) have significantly improve performance in image comprehension tasks, such as formatted charts and rich-content images. Yet,…