3 papers
cs.LG2025
Exploring the Potential of Large Language Models as Predictors in Dynamic Text-Attributed Graphs
Runlin Lei, Jiarui Ji, Haipeng Ding +4
With the rise of large language models (LLMs), there has been growing interest in Graph Foundation Models (GFMs) for graph-based tasks. By leveraging LLMs as predictors, GFMs have…
cs.LG2025
Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report
Haipeng Ding, Zhewei Wei, Yuhang Ye
Graph Neural Networks (GNNs) play a pivotal role in graph-based tasks for their proficiency in representation learning. Among the various GNN methods, spectral GNNs employing polyn…
cs.AI2020
Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs
Jing Zhang, Bo Chen, Lingxi Zhang +2
Knowledge graph reasoning is the fundamental component to support machine learning applications such as information extraction, information retrieval, and recommendation. Since kno…