13 citations · 18 across the 4 of their papers we have counts for
4 papers
CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer
Ankang Yang, Jitao Zhao, Di Jin +2
Graph foundation models (GFMs) have emerged as a promising paradigm for transferring knowledge across graph domains and tasks. Real-world graphs associate nodes with text, images,…
One Prompt Fits All: Universal Graph Adaptation for Pretrained Models
Yongqi Huang, Jitao Zhao, Dongxiao He +5
Graph Prompt Learning (GPL) has emerged as a promising paradigm that bridges graph pretraining models and downstream scenarios, mitigating label dependency and the misalignment bet…
Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily
Tao Wang, Rui Wang, Di Jin +2
Graph Convolutional Networks (GCNs) have been widely applied in various fields due to their significant power on processing graph-structured data. Typical GCN and its variants work…
An Ant-Based Algorithm with Local Optimization for Community Detection in Large-Scale Networks
Dongxiao He, Jie Liu, Bo Yang +3
In this paper, we propose a multi-layer ant-based algorithm MABA, which detects communities from networks by means of locally optimizing modularity using individual ants. The basic…