3 papers
cs.CV2026
Look Clearly Before Answering: Mitigating Hallucinations in LVLMs via Saliency-Driven Perceptual Realignment
Pengxu Chen, Yao Zhu, Guangming Zhu +4
Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding. However, they remain prone to hallucinations, generating responses that…
cs.CV2025
Towards Understanding How Knowledge Evolves in Large Vision-Language Models
Sudong Wang, Yunjian Zhang, Yao Zhu +4
Large Vision-Language Models (LVLMs) are gradually becoming the foundation for many artificial intelligence applications. However, understanding their internal working mechanisms h…
cs.LG2024
Know2Vec: A Black-Box Proxy for Neural Network Retrieval
Zhuoyi Shang, Yanwei Liu, Jinxia Liu +3
For general users, training a neural network from scratch is usually challenging and labor-intensive. Fortunately, neural network zoos enable them to find a well-performing model f…