Node Classification on Citeseer 1-shot
62.31AccuracyMTG
Evaluation results
| Method | Links | |
|---|---|---|
| MTG2026.06 | 62.31 | |
| GPF-plus2026.06 | 59.67 | |
| R-GFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 57.54 | |
| Gprompt2026.06 | 53.21 | |
| All-in-one2026.06 | 40.41 | |
| GCOPEParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 38.62 | |
| GPPT2026.06 | 37.26 | |
| Fine-tuning2026.06 | 35.05 | |
| DGIParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 34.52 | |
| GPPTParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 33.24 | |
| RiemannGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 31.86 | |
| GPF2026.06 | 31.16 | |
| G2PMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 31.04 | |
| GPMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 29.88 | |
| SAMGPTParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 28.78 | |
| GraphACLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 28.34 | |
| GraphPrompt+Paradigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 28.28 | |
| GraphCLParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 27.56 | |
| GPFParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 27.16 | |
| GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 26.89 | |
| GATParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 25.27 | |
| H2GCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 24.47 | |
| MDGFMParadigm=Graph Foundation Models, Setup=1-shot2026.05 | 23.32 | |
| Supervised2026.06 | 21.78 | |
| MixHopParadigm=Self-Supervised Pretraining with Fine-tuning, Setup=1-shot2026.05 | 21.35 | |
| FAGCNParadigm=Task-Supervised GNNs, Setup=1-shot2026.05 | 20.56 | |
| GraphPromptParadigm=Prompt-based Adaptation, Setup=1-shot2026.05 | 19.8 |