Image Classification on CIFAR-100 Class imbalance (test)
23.31AccuracyREFINE
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| REFINEBackbone=CNNs2025.05 | 23.31 | 0.8719 | 0.2264 | 40 | |
| AdapterBackbone=CNNs2025.05 | 22.66 | 0.8676 | 0.2102 | 0 | |
| LoRABackbone=CNNs2025.05 | 22.56 | 0.8535 | 0.2129 | 0 | |
| LinearProbeBackbone=CNNs2025.05 | 22.41 | 0.8687 | 0.2133 | 0 | |
| DANN-GateBackbone=CNNs2025.05 | 20.72 | 0.8432 | 0.1966 | 0 | |
| DistillBackbone=CNNs2025.05 | 19.59 | 0.8659 | 0.1752 | 0 | |
| NoTransBackbone=CNNs2025.05 | 17.58 | 0.8271 | 0.1656 | 100 |