Node Classification on Computers 10-shot
81.32AccuracyLEAP
Evaluation results
| Method | Links | ||
|---|---|---|---|
| LEAPPre-training strategy=ContraEdge2025.12 | 81.32 | 78.21 | |
| SUPTsoftPre-training strategy=ContraEdge2025.12 | 81.03 | 76.31 | |
| RELIEFPre-training strategy=ContraEdge2025.12 | 80.98 | 77.85 | |
| GPF-plusPre-training strategy=ContraEdge2025.12 | 80.85 | 77.05 | |
| GPFPre-training strategy=ContraEdge2025.12 | 80.2 | 76.91 | |
| SUPThardPre-training strategy=ContraEdge2025.12 | 80.2 | 76.43 | |
| FTPre-training strategy=ContraEdge2025.12 | 80.02 | 76.25 | |
| LEAPPre-training strategy=MaskedEdge2025.12 | 75.48 | 71.09 | |
| GPF-plusPre-training strategy=MaskedEdge2025.12 | 75.22 | 72.02 | |
| FTPre-training strategy=MaskedEdge2025.12 | 74.61 | 70.52 | |
| GPPTPre-training strategy=MaskedEdge2025.12 | 73.8 | 68.64 | |
| GPFPre-training strategy=MaskedEdge2025.12 | 73.29 | 68.03 | |
| RELIEFPre-training strategy=MaskedEdge2025.12 | 73.02 | 69.97 | |
| SUPThardPre-training strategy=MaskedEdge2025.12 | 72.56 | 68.2 | |
| SUPTsoftPre-training strategy=MaskedEdge2025.12 | 72.28 | 67.91 | |
| GPromptPre-training strategy=ContraEdge2025.12 | 69.81 | 67.13 |