39 citations · 43 across the 8 of their papers we have counts for
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cs.CV2026
ContraSafe-VL: A Contrastive Safety Preference Dataset for Vision-Language Models
Di Wu, Yanyan Zhao, Xin Lu +3
Vision-Language Models (VLMs) are increasingly deployed as general-purpose multimodal assistants, making multimodal safety alignment an important challenge. Safety depends on the i…
cs.CL2026
SocialPersona: Benchmarking Personalized Profiling and Response with Multimodal Social-Media Context
Qinkai Zhang, Yanyan Zhao, Xin Lu +3
Personalized language-model assistants are often evaluated through a memory lens: can a model recall preferences users have explicitly stated in dialogue? More comprehensive person…
cs.AI2026
STAR-S: Improving Safety Alignment through Self-Taught Reasoning on Safety Rules
Di Wu, Yanyan Zhao, Xin Lu +2
Defending against jailbreak attacks is crucial for the safe deployment of Large Language Models (LLMs). Recent research has attempted to improve safety by training models to reason…