Dataset B
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Root Cause Localization | Dataset B | Acc@175.66 | 19 | |
| Ultrasound Image Segmentation | Dataset B | Dice Score88.78 | 19 | |
| Ultrasound Tumor Segmentation | Dataset B | Dice Score88.78 | 19 | |
| Fault Types Classification | Dataset B | Micro Precision85 | 16 | |
| Breast Tumor Segmentation | Dataset B (val) | Dice Score88.5 | 16 | |
| Temporal Link Prediction | Dataset B WSDM 2022 Challenge | Initial AUC0.6504 | 12 | |
| Robotic Manipulation | Dataset B Gentle force condition 1.0 | Success Rate (SR)52 | 9 | |
| Robotic Manipulation | Dataset B force condition 1.0 (Firm) | Success Rate (SR)87 | 9 | |
| Ancient inscription restoration | Dataset B | SSIM91.33 | 9 | |
| Ancient Inscription Restoration | Dataset B | LPIPS (VGG)0.1076 | 9 | |
| Text Recovery | Dataset B (test) | Text Recovery Score73.78 | 9 | |
| Ancient Inscription Texture Restoration | Dataset B | PSNR37.5612 | 9 | |
| Ancient Inscription Restoration | Dataset B | Log-scaled Levenshtein Similarity0.3973 | 9 | |
| Ancient Inscription Restoration | Dataset B | Levenshtein Distance32.5556 | 9 | |
| Ancient Inscription Restoration | Dataset B | LPIPS0.0927 | 9 | |
| HBP Synthesis | Dataset B | CNR0.9363 | 5 | |
| MRI Synthesis | Dataset B | MAE12.4053 | 5 | |
| Source Count Estimation | Dataset B BRUDEX (test) | Accuracy91.9 | 5 | |
| Surface Normal Estimation | Dataset B (test) | MAE13.69 | 4 | |
| Reconstruction | Dataset B (held-out) | Mean Error0.136 | 2 | |
| Autonomous rollout classification | Dataset B osc. sep. | Mean Train Acc99.15 | 1 | |
| Vertical Ground Reaction Force Estimation | Dataset B | Metric- | 0 |
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