3 papers
cs.LG2026
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
Xiang Li, Jianpeng Qi, Haobing Liu +6
Graph Neural Networks (GNNs) have demonstrated impressive performance across diverse graph-based tasks by leveraging message passing to capture complex node relationships. However,…
cs.CL2025
LLMAtKGE: Large Language Models as Explainable Attackers against Knowledge Graph Embeddings
Ting Li, Yang Yang, Yipeng Yu +3
Adversarial attacks on knowledge graph embeddings (KGE) aim to disrupt the model's ability of link prediction by removing or inserting triples. A recent black-box method has attemp…
cs.DB2025
Efficient Discovery of Motif Transition Process for Large-Scale Temporal Graphs
Zhiyuan Zheng, Jianpeng Qi, Jiantao Li +3
Understanding the dynamic transition of motifs in temporal graphs is essential for revealing how graph structures evolve over time, identifying critical patterns, and predicting fu…