Multiple Datasets
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Few-Shot Segmentation | Multiple Datasets | Inference Time (ms)47 | 105 | |
| Active Learning | Multiple Datasets (test) | AULC58.82 | 33 | |
| Active Learning | Multiple Datasets (val) | LL58.37 | 33 | |
| Class-Incremental Learning | Multiple Datasets (CIFAR-100 and ImageNet-A) | Accuracy (Last Task)88.32 | 24 | |
| Regression | Multiple datasets | Pearson r0.635 | 15 | |
| Classification | Multiple datasets | Pearson r0.771 | 12 | |
| General Multimodal Intelligence | Multiple Datasets Average | Relative Score100 | 12 | |
| Classification | Multiple Datasets Aggregate | Accuracy91.17 | 10 | |
| Topology-Preservation | Multiple datasets mean Friedman rank (10 stratified outer folds) | Mean Friedman Rank (Betti H0)2.53 | 9 | |
| Time Series Imputation | Multiple datasets 91 d | Win counts5 | 6 | |
| Time Series Imputation | Multiple datasets 30 d | Win Counts6 | 6 | |
| Time Series Imputation | Multiple datasets 7 d | Win Counts7 | 6 | |
| Synthetic Data Privacy Evaluation | Multiple datasets Average | Discriminator AUC0.91 | 5 | |
| Single-View Depth Estimation | Multiple Datasets | Average Rank2.2 | 4 | |
| Image Forgery Detection | Multiple Datasets | Accuracy90.1 | 1 | |
| Watermark Removal | Multiple datasets | Metric- | 0 |
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