D2
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | D2 | Mean Accuracy91.611 | 30 | |
| Aspect Sentiment Triplet Extraction | D2 (16Res) | F1 Score74.83 | 25 | |
| Aspect Sentiment Triplet Extraction | D2 15Res | F1 Score66.12 | 25 | |
| Aspect Sentiment Triplet Extraction | D2 14Lap | F1 Score63.61 | 25 | |
| Aspect Sentiment Triplet Extraction | D2 14Res | F1 Score75.59 | 25 | |
| Time Series Forecasting | D2 Synthetic (test) | MSE0.599 | 16 | |
| Medical Image Segmentation | D2 | DSC87.35 | 14 | |
| Regression | D2 | Average Relative MSE0.084 | 10 | |
| Classification | D2 0.15 (test) | Mean Accuracy91.657 | 10 | |
| ICD-10 Code Prediction | D2 noisy (test) | AUPRC (Z37)93.86 | 10 | |
| Outlier Detection | D2 with only clusteriers (test) | AUC0.918 | 9 | |
| Aspect-level sentiment classification | D2 | Accuracy72.08 | 9 | |
| Knee cartilage segmentation | D2 | Dice94.14 | 7 | |
| Root Cause Localization | D2 complete data conditions | Top-1 Accuracy81.5 | 7 | |
| Failure Triage | D2 complete data conditions | Precision88.2 | 6 | |
| Anomaly Detection | D2 complete data conditions | Precision99.3 | 6 | |
| Time-Domain Prediction | D2 | NMSE (dB)-18.58 | 6 | |
| Reliability Assessment | D2 (test) | AU-ARC92.1 | 5 | |
| Frequency-Domain Prediction | D2 | NMSE (dB)-8.95 | 5 | |
| Trajectory Planning | D2 OOD-OV | RRPI3,103.8 | 4 | |
| Trajectory Planning | D2 OOD | RRPI4,372.4 | 4 | |
| CSI Reconstruction | D2 | NMSE (dB)-15.91 | 3 | |
| Root Cause Localization | D2 (test) | Execution Time (s)8.08 | 2 | |
| Failure Triage | D2 (test) | Execution Time (s)1.45 | 2 | |
| Anomaly Detection | D2 (test) | Execution Time (s)6.71 | 2 |
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