graph foundation models 1hierarchical context modeling 1large language models 1multimodal graphs 1zero-shot transfer 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.AI2026
CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer
Ankang Yang, Jitao Zhao, Di Jin +2
The paper introduces CHARM, a multimodal graph foundation model that uses hierarchical context modeling to enable zero-shot transfer across graph domains without fine-tuning. It en…
cs.LG2025
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…
cs.LG2025
Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling
Yongqi Huang, Jitao Zhao, Dongxiao He +3
Graph Contrastive Learning (GCL) aims to self-supervised learn low-dimensional graph representations, primarily through instance discrimination, which involves manually mining posi…