4 papers
Revisiting General Map Search via Generative Point-of-Interest Retrieval
Dong Chen, Shuai Zheng, Haoyang Shao +5
Point-of-Interest (POI) retrieval aims to identify relevant candidates from massive-scale POI databases, serving as a cornerstone for diverse location-based services. However, in g…
Position: Spectral GNNs Are Neither Spectral Nor Superior for Node Classification
Qin Jiang, Chengjia Wang, Michael Lones +2
Spectral Graph Neural Networks (Spectral GNNs) for node classification promise frequency-domain filtering on graphs, yet rest on flawed foundations. Recent work shows that graph La…
Towards Pre-trained Graph Condensation via Optimal Transport
Yeyu Yan, Shuai Zheng, Wenjun Hui +5
Graph condensation (GC) aims to distill the original graph into a small-scale graph, mitigating redundancy and accelerating GNN training. However, conventional GC approaches heavil…
Dynamic Graph Condensation
Dong Chen, Shuai Zheng, Yeyu Yan +4
Recent research on deep graph learning has shifted from static to dynamic graphs, motivated by the evolving behaviors observed in complex real-world systems. However, the temporal…