Jun-Qi Liu

AUGKD: Adaptive Universal Graph Knowledge Distillation

Graph data distillation frameworks have shown great potential in compressing graph representations and improving learning efficiency. Nevertheless, their robustness and generalization remain limited when applied to different graph neural network architectures. To address these limitations, we propose Adaptive Universal...