1 INTRODUCTION

2 PRELIMINARY

3 PRETEXTS FOR MICROSCOPIC KNOWLEDGE  
3.1 Node Features  
3.2 Node Properties  
3.3 Links  

4 PRETEXTS FOR MESOSCOPIC KNOWLEDGE  
4.1 Context  
4.2 Long-Range Similarities  
4.3 Motifs  
4.4 Clusters  

5 PRETEXTS FOR MACROSCOPIC KNOWLEDGE  
5.1 Global Structure  
5.2 Manifolds  

6 DOWNSTREAM TASK GENERALIZATION  
6.1 Fine-tuning  
6.2 Probing  
6.3 Prompting  

7 SELF-SUPERVISED GRAPH LANGUAGE MODELS  
7.1 Textual knowledge-aware graph models  
7.2 Graph knowledge-aware language models  

8 FUTURE DIRECTIONS  
8.1 Deeper and wider graph knowledge discovery  
8.2 Combining different types of graph knowledge  
8.3 Theoretical frameworks for GFMs  
8.4 Expanding graph data and evaluation procedures  
8.5 Unifying knowledge scopes for emergent ability