| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Roman-empire | FedGTA | Time Consumption (s)2.17 | 84 | 26d ago | |
| Cora | AdaFGL | Time Consumption (s)1.99 | 84 | 26d ago | |
| Fashion-MNIST (val) | FedAvg | Error Rate9 | 80 | 1mo ago | |
| Shakespeare (val) | AdaBFL | Perplexity3.721 | 73 | 1mo ago | |
| MNIST Severe Non-IID (Dirichlet α = 0.1) | FOFedAvg | Communication Rounds4 | 33 | 3mo ago | |
| MNIST Severe Non-IID | FOFedAvg | Communication Cost (MB)24 | 33 | 3mo ago | |
| Shakespeare | FEDADAVR-QUANT | Accuracy50.611 | 33 | 3mo ago | |
| ACSIncome | Clust-PSI-PFL | Local Average Distance (AD)0.01 | 30 | 3mo ago | |
| CIFAR-100 | FedFew | Jain's Fairness Index99.7 | 21 | 2mo ago | |
| CIFAR-10 | Ditto | Jain's Fairness Index0.997 | 21 | 2mo ago | |
| CIFAR-100 500 clients, 1% participation Dirichlet 0.3 (train test) | FedACG | Accuracy (500 Rounds)31.74 | 13 | 3mo ago | |
| CIFAR-10 500 clients, 1% participation Dirichlet 0.3 (train test) | MOON | Accuracy (500 Rounds)64.55 | 13 | 3mo ago | |
| Tiny-ImageNet (test) | FedACG | Accuracy (500R)31.47 | 13 | 3mo ago | |
| CIFAR-10 (test) | FedACG | Accuracy (500R)73.61 | 13 | 3mo ago | |
| CIFAR-100 100 clients Dirichlet 0.3 | FedACG | Accuracy (500 Rounds)49.56 | 13 | 3mo ago | |
| CIFAR-10 100 clients Dirichlet 0.3 | FedDC | Accuracy (Round 500)77.76 | 13 | 3mo ago | |
| PERCEPT-R | FedSWA | Mean F1 Score79 | 12 | 2mo ago | |
| HugaDB | CurvFed | Mean F1 Score89.2 | 12 | 2mo ago | |
| Stress sensing | FedSAM | Mean F1 Score80 | 12 | 2mo ago | |
| WIDAR | FedAvg | Mean F1 Score86.2 | 12 | 2mo ago | |
| Serengeti | Clust-PSI-PFL | Local Avg Distance (AD)0.01 | 12 | 3mo ago | |
| EMNIST Cross-device | SgnG | Aθ Score75.87 | 10 | 1mo ago | |
| NASA Bearings Label Skew (downstream) | Empirical Best | Weighted Accuracy69.48 | 10 | 1mo ago | |
| Dolly-15K | FedHDS-Turbo | Speedup18.86 | 10 | 3mo ago | |
| Natural Instructions (NI) | FedHDS-Turbo | Speedup48.8 | 10 | 3mo ago |
