Chameleon
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Node Classification | Chameleon | Accuracy85.86 | 640 | |
| Node classification | Chameleon (test) | Mean Accuracy80.17 | 297 | |
| Camouflaged Object Detection | CHAMELEON | S-measure (S_alpha)93.3 | 150 | |
| AI-generated image detection | Chameleon | Accuracy92.4 | 107 | |
| AI-generated image detection | Chameleon (test) | Accuracy85.57 | 74 | |
| Node Classification | Chameleon (60%/20%/20% random) | Accuracy76.08 | 72 | |
| Camouflaged Object Detection | CHAMELEON (test) | F-beta Score0.885 | 66 | |
| Node Classification | Chameleon h=0.23 (test) | Mean Accuracy72.13 | 56 | |
| Node Classification | Chameleon (48/32/20) | Mean Accuracy79.6 | 49 | |
| Node Classification | Chameleon (filtered splits) | Accuracy44.9 | 43 | |
| Node Classification | Chameleon (fixed) | Accuracy68.42 | 42 | |
| Node Classification | Chameleon Standard (test) | Accuracy72.66 | 33 | |
| Node Classification | Chameleon (10 different splits) | Accuracy71.38 | 30 | |
| Camouflaged Object Segmentation | CHAMELEON | Fw_beta89.5 | 28 | |
| Node Classification | Chameleon dense original | Accuracy79.84 | 26 | |
| Edge Unlearning | Chameleon (hard) | Trade-off of Unlearning (ToU)82.22 | 25 | |
| Node Classification | Chameleon Undirected (test) | Accuracy73.6 | 23 | |
| Camouflaged Object Detection | CHAMELEON | MAE0.017 | 22 | |
| Node Classification | Chameleon full-supervised | Accuracy72.52 | 22 | |
| Camouflaged Object Detection | CHAMELEON 50 (test) | M0.207 | 21 | |
| Node classification | Chameleon | Accuracy73 | 20 | |
| Node unlearning | Chameleon | Average Runtime (s)0.02 | 20 | |
| Node Classification | Chameleon Heterophilous Dataset (train-val-test) | Accuracy60.11 | 20 | |
| Node Regression | Chameleon | Normalized MAE Loss0.484 | 20 | |
| Camouflaged Object Segmentation | CHAMELEON 87 (test) | Fw_beta90.2 | 19 |
Showing 25 of 73 rows