| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Fashion MNIST (test) | Accuracy97.9 | 592 | |
| Image Classification | Fashion-MNIST | Accuracy100 | 300 | |
| Image Classification | Fashion MNIST | Accuracy98.8 | 240 | |
| Clustering | Fashion-MNIST | NMI80 | 107 | |
| Image Classification | Fashion-MNIST | TER12 | 77 | |
| Image Classification | Fashion-MNIST (test) | Accuracy (%)96.93 | 55 | |
| Image Classification | Fashion-MNIST 50-client (Non-IID) | Error Rate11.2 | 49 | |
| Image Classification | Fashion-MNIST IID 50-client | Error Rate10.3 | 49 | |
| Image Classification | Fashion-MNIST uniform noise η=0.5 (7-fold CV) | Accuracy84.36 | 43 | |
| Image Classification | Fashion-MNIST uniform noise η=0.4 (7-fold CV) | Accuracy86.29 | 43 | |
| Image Classification | Fashion-MNIST uniform noise η=0.3 (7-fold CV) | Accuracy87.45 | 43 | |
| Image Classification | Fashion-MNIST uniform noise η=0.2 (7-fold CV) | Accuracy88.32 | 43 | |
| Image Classification | Fashion-MNIST uniform noise η=0.1 (7-fold CV) | Accuracy88.92 | 43 | |
| Model Fingerprinting | Fashion-MNIST | AUC99.2 | 40 | |
| Anomaly Detection | Fashion-MNIST | Avg AUC95.6 | 40 | |
| Image Generation | Fashion-MNIST | FID1.49 | 38 | |
| Image Classification | Fashion-MNIST (val) | Accuracy95.56 | 37 | |
| VAE Log-Likelihood Estimation | Fashion MNIST (test) | Log-Likelihood-233.39 | 30 | |
| Generative Modeling | Fashion MNIST (train) | Log Likelihood (100 samples)-230.77 | 30 | |
| kNN Classification | Fashion-MNIST | Accuracy81.8 | 30 | |
| Federated Learning Fairness | Fashion MNIST (test) | Accuracy Variance1.005 | 28 | |
| Deep Clustering | Fashion-MNIST (test) | SC0.922 | 28 | |
| Image Classification | Fashion-MNIST Dir(0.5) (test) | Accuracy90.49 | 28 | |
| Image Classification | Fashion-MNIST under sudden drift and Dir(0.1) 1.0 (test) | Accuracy (Generalized)87.63 | 28 | |
| Image Classification | Fashion-MNIST Dir(0.5) | Accuracy90.57 | 28 |