4 papers
Neural Gate: Mitigating Privacy Risks in LVLMs via Neuron-Level Gradient Gating
Xiangkui Cao, Jie Zhang, Meina Kan +2
Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in critical domains such as finance and…
VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model
Sibo Wang, Xiangkui Cao, Jie Zhang +4
The emergence of Large Vision-Language Models (LVLMs) marks significant strides towards achieving general artificial intelligence. However, these advancements are accompanied by co…
Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models
Jie Zhang, Xiangkui Cao, Zhouyu Han +2
Large Vision-Language Models (LVLMs) exhibit impressive potential across various tasks but also face significant privacy risks, limiting their practical applications. Current resea…
REVAL: A Comprehension Evaluation on Reliability and Values of Large Vision-Language Models
Jie Zhang, Zheng Yuan, Zhongqi Wang +6
The rapid evolution of Large Vision-Language Models (LVLMs) has highlighted the necessity for comprehensive evaluation frameworks that assess these models across diverse dimensions…