Xingping Xian
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126
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ML×1AI×1
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2026
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
GJDNet proposes a joint disentanglement framework to enhance the robustness of Graph Neural Networks against adversarial attacks by simultaneously stabilizing node representations and decision boundaries across diverse graph connectivity types.
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Papers
cs.LGcs.AIRecentJun 1, 2026
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
Canyixing Cui, Tao Wu, Xingping Xian, Xiao-Ke Xu +2 more
GJDNet proposes a joint disentanglement framework to enhance the robustness of Graph Neural Networks against adversarial attacks by simultaneously stabilizing node representations and decision boundar…
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