Node Classification on TAX
73.21Mean AccuracyCLDG++
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CLDG++Input=X, A, S, T, Training Paradigm=Unsupervised2026.05 | 73.21 | 73.01 | |
| GCNInput=X, A, Y, Training Paradigm=Supervised2026.05 | 71.65 | 71.37 | |
| CLDGInput=X, A, T, Training Paradigm=Unsupervised2026.05 | 69.62 | 69.18 | |
| MVGRLInput=X, A, S, Training Paradigm=Unsupervised2026.05 | 67.7 | 67.08 | |
| CCA-SSGInput=X, A, Training Paradigm=Unsupervised2026.05 | 67.62 | 67.14 | |
| GRACEInput=X, A, Training Paradigm=Unsupervised2026.05 | 67.43 | 66.79 | |
| DGIInput=X, A, Training Paradigm=Unsupervised2026.05 | 66.57 | 65.87 | |
| GraphSAGEInput=X, A, Y, Training Paradigm=Supervised2026.05 | 64.36 | 63.73 | |
| GATInput=X, A, Y, Training Paradigm=Supervised2026.05 | 62 | 59.78 | |
| CAWInput=X, A, T, Training Paradigm=Unsupervised2026.05 | 53.25 | 47.11 | |
| DySATInput=X, A, T, Training Paradigm=Unsupervised2026.05 | 52.31 | 51.42 | |
| TGATInput=X, A, T, Training Paradigm=Unsupervised2026.05 | 50.12 | 45.62 | |
| MNCIInput=X, A, T, Training Paradigm=Unsupervised2026.05 | 45.44 | 37.13 | |
| LPInput=A, Y, Training Paradigm=Supervised2026.05 | 35.67 | 30.88 |