3 papers
cs.CV2026
Adaptive Disentangled Representation Learning for Incomplete Multi-View Multi-Label Classification
Quanjiang Li, Zhiming Liu, Tianxiang Xu +2
Multi-view multi-label learning frequently suffers from simultaneous feature absence and incomplete annotations, due to challenges in data acquisition and cost-intensive supervisio…
cs.LG2025
Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation
Zhangqi Jiang, Tingjin Luo, Xu Yang +1
View missing remains a significant challenge in graph-based multi-view semi-supervised learning, hindering their real-world applications. To address this issue, traditional methods…
cs.CV2025
Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens
Zhangqi Jiang, Junkai Chen, Beier Zhu +3
Hallucinations in Large Vision-Language Models (LVLMs) significantly undermine their reliability, motivating researchers to explore the causes of hallucination. However, most studi…