Image Classification on CIFAR-100 (beta=0.5)
83.31AccuracyGGEUR
Evaluation results
| Method | Links | |
|---|---|---|
| GGEURBackbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 83.31 | |
| FedFA (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedFA2025.03 | 81.98 | |
| FedAvg (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 81.41 | |
| FedMix (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedMix2025.03 | 81.31 | |
| FEDGEN (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FEDGEN2025.03 | 81.24 | |
| FedCLIPFederated Learning Algorithm=FedCLIP2025.03 | 72.03 | |
| FedTPGFederated Learning Algorithm=FedTPG2025.03 | 71.4 | |
| Zero-Shot CLIPBackbone=CLIP, Mode=Zero-Shot2025.03 | 64.87 |