Node Classification on Computers 1-shot
52.3AccuracyR-GFM
Evaluation results
| Method | Links | |
|---|---|---|
| R-GFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 52.3 | |
| G2PMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 51.92 | |
| GPMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 48.58 | |
| RiemannGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 46.2 | |
| SAMGPTParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 45.8 | |
| GPPTParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 44.57 | |
| GraphACLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 44.42 | |
| GraphPrompt+Paradigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 43.01 | |
| MDGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 42.68 | |
| GPFParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 42.15 | |
| GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 39.43 | |
| GATParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 38.05 | |
| DGIParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 34.59 | |
| GraphCLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 34.4 | |
| GraphPromptParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 33.34 | |
| MixHopParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 29.77 | |
| GCOPEParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 28.5 | |
| FAGCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 27.02 | |
| H2GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 19.29 |