3 papers
cs.CV2026
Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model
Sibo Wang, Jie Zhang, Shiguang Shan +2
While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulnerable to adversarial attacks…
cs.CV2026
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…
cs.CV2025
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…