1 Introduction
2 Background
2.1 Deep Graph Learning
2.2 Language Foundation Models
3 Graph Foundation Models
3.1 Concepts of Graph Foundation Model
3.2 Comparison with Language Foundation Model
3.3 Summary
4 GNN-Based Models
4.1 Backbone Architectures
4.2 Pre-training
4.3 Adaptation
4.4 Discussion
5 LLM-Based Models
5.1 Backbone Architectures
5.2 Pre-Training
5.3 Adaptation
5.4 Discussion
6 GNN + LLM-Based Models
6.1 Backbone Architectures
6.2 Pre-training
6.3 Adaptation
6.4 Discussion
7 Challenges and Future Directions
7.1 Challenges about Data and Evaluation
7.2 Challenges about Model
7.3 Challenges about Applications
8 Conclusions