11 citations · 16 across the 5 of their papers we have counts for
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cs.LG2025★ 1 cited
Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling
Xin He, Yili Wang, Yiwei Dai +1
Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to become indistinguishable. While e…
cs.LG2025★ 4 cited
Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space
Xin He, Yili Wang, Wenqi Fan +4
Graph Neural Networks (GNNs) have shown great success in various graph-based learning tasks. However, it often faces the issue of over-smoothing as the model depth increases, which…
cs.LG2025
Graph Defense Diffusion Model
Xin He, Wenqi Fan, Yili Wang +4
Graph Neural Networks (GNNs) are highly vulnerable to adversarial attacks, which can greatly degrade their performance. Existing graph purification methods attempt to address this…