Fangbing Liu

2 accepted papers

2026

AdaSpec: Adaptive Spectrum for Enhanced Node Distinguishability

ICLR 2026poster

Spectral Graph Neural Networks (GNNs) achieve strong performance in node classification, yet their node distinguishability remains poorly understood. We analyze how graph matrices and node features jointly influence node distinguishability. Further, we derive a theoretical lower bound on the number…

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2025

Asymmetric Learning for Spectral Graph Neural Networks

Fangbing Liu, Qing Wang

AAAI 2025technical

Optimizing spectral graph neural networks (GNNs) remains a critical challenge in the field, yet the underlying processes are not well understood. In this paper, we investigate the inherent differences between graph convolution parameters and feature transformation parameters in spectral GNNs and th…

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