Multi-label Node Classification on DBLP node split (6:2:2)
94.38Macro AUCGCN+LIP
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| GCN+LIPBackbone=GCN, Multi-label processing=Label Influence Propagation2026.07 | 94.38 | 87.45 | |
| VariMul2026.07 | 92.14 | 85.3 | |
| GCN+AutoBackbone=GCN, Multi-label processing=Auto2026.07 | 92.13 | 85.48 | |
| LANC2026.07 | 91.68 | 83.5 | |
| GCN+ML-KNNBackbone=GCN, Multi-label processing=ML-KNN2026.07 | 90.11 | 80.01 | |
| GCN+PLAINBackbone=GCN, Multi-label processing=PLAIN2026.07 | 80.55 | 73.44 | |
| LARN2026.07 | 74.29 | 58.11 | |
| MLGW2026.07 | 73.32 | 56.03 | |
| ML-GCN2026.07 | 72.66 | 56.71 | |
| Node2vec+CCBackbone=Node2vec, Multi-label processing=Classifier Chains (CC)2026.07 | 72.57 | 57.13 | |
| Node2vec+BRBackbone=Node2vec, Multi-label processing=Binary Relevance (BR)2026.07 | 71.22 | 57.41 |