Digits
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Digits-Five | Accuracy (Source: mt)99.5 | 67 | |
| Classification | Digits (test) | Average Accuracy89.91 | 59 | |
| Domain Generalization | Digits-DG | Accuracy96.38 | 50 | |
| Classification | Digits UCI (test) | Error Rate0.078 | 39 | |
| Classification | Digits | Macro-F1100 | 36 | |
| Digit Recognition | Digits SVHN, MNIST, USPS (test) | Average Accuracy98.8 | 29 | |
| Scalability analysis | Digits | Per-iteration Wall-Clock Time (ms)1 | 25 | |
| Image Classification | Digits | Accuracy (SVHN Source)94.57 | 25 | |
| Clustering | digits | ARI0.9 | 23 | |
| Image Classification | Digits | Average Accuracy97.6 | 23 | |
| Hierarchical Agglomerative Clustering | digits | Dendrogram Purity90.4 | 20 | |
| Single-Source Domain Generalization | Digits (test) | Acc (MNIST-M)87.76 | 19 | |
| Multi-domain generalization | Digits-DG | Score M97.8 | 18 | |
| Counterfactual Explanation Generation | Digits | Validity100 | 17 | |
| Clustering | Digits (6V) | Accuracy97.45 | 16 | |
| Clustering | Digits (4V) | Accuracy (Digits 4V)96.5 | 16 | |
| Clustering | Digits (3V) | Accuracy (ACC)95.9 | 16 | |
| Clustering | Digits (2V) | Accuracy95.55 | 16 | |
| Domain Adaptation | Digits | Accuracy98.4 | 15 | |
| Image Classification | Digits (MNIST, USPS, SVHN, MNIST-M) standard (test) | Source Drop4.2 | 15 | |
| Classification | Digits | Accuracy97.3 | 13 | |
| Node Classification | Digits (test) | Accuracy92.5 | 13 | |
| Object Recognition | Digits MNIST USPS SVHN SYN | Accuracy (MNIST)98.55 | 12 | |
| Classification | Digits (train) | Training Loss0.1129 | 12 | |
| Off-Policy Evaluation | Digits (UCI) | MSE0.0006 | 12 |
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