Node Classification on OGBN-MAG
54.21Accuracy/F1 ScoreHGUL
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| HGULGraph Learning Type=Heterogeneous, Heterophily Awareness=Yes2026.04 | 54.21 | — | — | |
| H2G-formerGraph Learning Type=Heterogeneous, Heterophily Awareness=Yes2026.04 | 53.12 | — | — | |
| Hetero2NetGraph Learning Type=Heterogeneous, Heterophily Awareness=Yes2026.04 | 51.6 | — | — | |
| R-GraphSAGEGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 50.94 | — | — | |
| HGTGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 50.23 | — | — | |
| HDHGRGraph Learning Type=Heterogeneous, Heterophily Awareness=Yes2026.04 | 49.21 | — | — | |
| GATGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 48.6 | — | — | |
| MixHopGraph Learning Type=Homogeneous, Heterophily Awareness=Yes2026.04 | 46.99 | — | — | |
| R-GCNGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 46.93 | — | — | |
| LatGRLGraph Learning Type=Heterogeneous, Heterophily Awareness=Yes2026.04 | 46.07 | — | — | |
| Simple-HGNGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 43.39 | — | — | |
| GCNGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 42.9 | — | — | |
| NAGphormerGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 42.47 | — | — | |
| R-GATGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 41.51 | — | — | |
| LINKXGraph Learning Type=Homogeneous, Heterophily Awareness=Yes2026.04 | 40.83 | — | — | |
| GraphSAGEGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 40.8 | — | — | |
| HANGraph Learning Type=Heterogeneous, Heterophily Awareness=No2026.04 | 39 | — | — | |
| APPNPGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 37.64 | — | — | |
| GINGraph Learning Type=Homogeneous, Heterophily Awareness=No2026.04 | 37.32 | — | — | |
| A2QBackbone=GCN2026.01 | — | 32.7 | 2.7 | |
| FP32Backbone=GCN2026.01 | — | 33.6 | 32 | |
| GPF-PlusBackbone=GCN, Quantization Framework=A2Q2026.01 | — | 30.4 | 2.9 | |
| GraphSAGELearning Style=E2E2023.10 | — | 46.46 | — | |
| HGTLearning Style=E2E2023.10 | — | 46.78 | — | |
| LoRAPBackbone=GCN, Quantization Framework=A2Q2026.01 | — | 34.2 | 2.7 | |
| NARSLearning Style=Pre-computation2023.10 | — | 50.66 | — | |
| RGCNLearning Style=E2E2023.10 | — | 48.11 | — | |
| RpHGNNLearning Style=Pre-computation2023.10 | — | 52.07 | — | |
| SeHGNNLearning Style=Pre-computation2023.10 | — | 51.45 | — | |
| UniPromptBackbone=GCN, Quantization Framework=A2Q2026.01 | — | 31 | 2.9 |