2 papers
cs.CV2026
Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
Yutong Xie, Zhenglin Hua, Ran Wang +3
Large Vision-Language Models (LVLMs) have shown remarkable performance on a wide range of vision-language tasks. Despite this progress, they are still prone to hallucination, gener…
cs.LG2025
A Mathematics Framework of Artificial Shifted Population Risk and Its Further Understanding Related to Consistency Regularization
Xiliang Yang, Shenyang Deng, Shicong Liu +3
Data augmentation is an important technique in training deep neural networks as it enhances their ability to generalize and remain robust. While data augmentation is commonly used…