The Confidence Trap: Calibration Attacks for Graph Neural Networks
DGX agentarXiv:2606.08467v1 Announce Type: cross Abstract: While confidence calibration is essential for trustworthy decision-making in safety-critical applications, the robustness of calibrated GNNs to advers