3 papers
cs.LG2026
Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
Jiaqi Lv, Qingfeng Du, Yu Zhang +2
Graph Neural Networks (GNNs) have emerged as a powerful framework for processing graph-structured data. However, conventional GNNs and their variants are inherently limited by the…
cs.LG2026
Multi-Scale Adaptive Neighborhood Awareness Transformer For Graph Fraud Detection
Jiaqi Lv, Qingfeng Du, Yu Zhang +2
Graph fraud detection (GFD) is crucial for identifying fraudulent behavior within graphs, benefiting various domains such as financial networks and social media. Existing methods b…
cs.LG2025
FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning
Yu Zhang, Qingfeng Du, Jiaqi Lv
Federated Learning (FL) enables decentralized model training across multiple parties while preserving privacy. However, most FL systems assume clients hold only unimodal data, limi…