Wisconsin
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Node Classification | Wisconsin | Accuracy96 | 627 | |
| Node classification | Wisconsin (test) | Mean Accuracy94.89 | 239 | |
| Node Classification | Wisconsin (48/32/20) | Mean Accuracy92.54 | 66 | |
| Node Classification | Wisconsin (60%/20%/20%) | Test Accuracy98 | 43 | |
| Node Classification | Wisconsin H=0.19 | Accuracy82.15 | 39 | |
| Node Classification Robustness Certification | Wisconsin | Time (s) (All Instances)0.01 | 36 | |
| Classification | wisconsin | Accuracy97.5 | 35 | |
| node classification | wisconsin | Micro F112.8 | 32 | |
| Node Classification | Wisconsin standard (test) | Accuracy87.65 | 23 | |
| Node Classification | Wisconsin | Count65 | 22 | |
| Node Classification | Wisconsin (10 splits) | Accuracy89.41 | 22 | |
| Node Classification | Wisconsin (fixed) | Accuracy88.43 | 21 | |
| Node classification | Wisconsin (Wis.) | Accuracy87.6 | 20 | |
| Link Prediction | Wisconsin Attributed | AUC82.5 | 18 | |
| Node clustering | Wisconsin (test) | Conductance0.52 | 15 | |
| Classification | wisconsin 25% feature noise | Accuracy97 | 14 | |
| Classification | wisconsin | F1 Score97.7 | 14 | |
| Node Classification | Wisconsin original (test) | Accuracy85.01 | 14 | |
| Graph Clustering | Wisconsin | Accuracy74.1 | 13 | |
| Explainability | Wisconsin | Faithfulness (KL distance)0.006 | 12 | |
| Few-shot Graph Learning Explainability | Wisconsin (3% labeling ratio) | Explainability Performance6.75 | 12 | |
| Few-shot Graph Learning Explainability | Wisconsin (2% labeling ratio) | Explainability Performance2.29 | 12 | |
| Node Classification | Wisconsin heterophilic (test) | Accuracy82.31 | 12 | |
| Node classification | Wisconsin heterophilous (official) | Accuracy82.9 | 11 | |
| Link Prediction | Wisconsin (test) | Accuracy71.77 | 11 |
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