Node Classification on Wisconsin 1-shot
35.41AccuracyR-GFM
Evaluation Results
| Method | Links | |
|---|---|---|
| R-GFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 35.41 | |
| G2PMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 34.7 | |
| GraphCLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 32.16 | |
| RiemannGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 31.2 | |
| MixHopParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 29.82 | |
| GraphACLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 29.41 | |
| GPMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 29.19 | |
| GCOPEParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 28.69 | |
| DGIParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 28.24 | |
| FAGCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 26.19 | |
| GPPTParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 23.53 | |
| GPFParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 23.53 | |
| SAMGPTParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 21.57 | |
| GraphPromptParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 20.39 | |
| H2GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 20.34 | |
| MDGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 17.65 | |
| GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 17.46 | |
| GATParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 16.86 | |
| GraphPrompt+Paradigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 16.86 |