34 citations · 91 across the 21 of their papers we have counts for
22 papers
Contrastive Learning Meets Pseudo-label-assisted Mixup Augmentation: A Comprehensive Graph Representation Framework from Local to Global
Jinlu Wang, Yanfeng Sun, Jiapu Wang +3
Graph Neural Networks (GNNs) have demonstrated remarkable effectiveness in various graph representation learning tasks. However, most existing GNNs focus primarily on capturing loc…
Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
Yachao Yang, Yanfeng Sun, Jipeng Guo +4
Graph Neural Networks (GNNs) have excelled in handling graph-structured data, attracting significant research interest. However, two primary challenges have emerged: interference b…
Hierarchical Multi-modal Transformer for Cross-modal Long Document Classification
Tengfei Liu, Yongli Hu, Junbin Gao +2
Long Document Classification (LDC) has gained significant attention recently. However, multi-modal data in long documents such as texts and images are not being effectively utilize…
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations
Jinlu Wang, Jipeng Guo, Yanfeng Sun +4
Graph neural networks (GNNs) demonstrate a robust capability for representation learning on graphs with complex structures, showcasing superior performance in various applications.…
Adversarial Privacy-preserving Filter
Jiaming Zhang, Jitao Sang, Xian Zhao +3
While widely adopted in practical applications, face recognition has been critically discussed regarding the malicious use of face images and the potential privacy problems, e.g.,…
Attention, Please! Adversarial Defense via Activation Rectification and Preservation
Shangxi Wu, Jitao Sang, Kaiyuan Xu +2
This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change. In particular, we obs…