13 citations · 15 across the 7 of their papers we have counts for
4 papers · 1 filter
Rethinking Graph Domain Adaptation: A Spectral Contrastive Perspective
Haoyu Zhang, Yuxuan Cheng, Wenqi Fan +2
Graph neural networks (GNNs) have achieved remarkable success in various domains, yet they often struggle with domain adaptation due to significant structural distribution shifts a…
Towards Graph Foundation Models: A Transferability Perspective
Yuxiang Wang, Wenqi Fan, Suhang Wang +1
In recent years, Graph Foundation Models (GFMs) have gained significant attention for their potential to generalize across diverse graph domains and tasks. Some works focus on Doma…
Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation
Yuxiang Wang, Xinnan Dai, Wenqi Fan +1
In recent years, large language models (LLMs) have emerged as promising candidates for graph tasks. Many studies leverage natural language to describe graphs and apply LLMs for rea…
Graph Unlearning with Efficient Partial Retraining
Jiahao Zhang, Lin Wang, Shijie Wang +1
Graph Neural Networks (GNNs) have achieved remarkable success in various real-world applications. However, GNNs may be trained on undesirable graph data, which can degrade their pe…