ER
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Maximum Independent Set | ER [700-800] | Solution Size44.87 | 48 | |
| Emotion Recognition | ER | Accuracy66.1 | 33 | |
| Causal Discovery | ER5 n = 50, h = 5 synthetic | FDR4 | 15 | |
| Maximum Independent Set | ER [700-800] DIMES (test) | Approximation Ratio (ApR)1.006 | 11 | |
| Curvilinear Structure Segmentation | ER (test) | Dice Coefficient84.52 | 9 | |
| Node-level classification | ER 15K | MCC0.915 | 9 | |
| Robustness Prediction | ER (Dynamic) | Mean Error0.0005 | 8 | |
| Robustness Prediction | ER Static | Mean Error0.0028 | 8 | |
| Node-level classification | ER 30K | Accuracy76 | 7 | |
| Node-level classification | ER 30K | MCC0.872 | 7 | |
| Minimum Vertex Cover | ER (400,500) slice (test) | Avg Vertex Cover Size415.52 | 5 | |
| Minimum Vertex Cover | ER (100,200) (test) | Avg Vertex Cover Size122.76 | 5 | |
| Minimum Vertex Cover | ER (50,100) slice (test) | Avg Vertex Cover Size54.67 | 5 | |
| Maximum Independent Set | ER [9000-11000] | MIS Size381.31 | 5 | |
| Maximum Cut | ER (400,500) (test) | Avg Cut Size16,491.6 | 4 | |
| Causal Discovery | ER (30, 60) | SHD17.52 | 3 | |
| Causal Discovery | ER (10, 20) | SHD1.44 | 3 |
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