Image Classification on CIFAR-10-LT IF 100
89.1Top-1 AccuracyGLMC + Loss + LR
Evaluation Results
| Method | Links | |
|---|---|---|
| GLMC + Loss + LRreweighting=Inverse-view, LR Schedule=MiLeLR2026.05 | 89.1 | |
| GLMC + Lossreweighting=Inverse-view2026.05 | 88.6 | |
| B-SCLVenue=NeurIPS252026.05 | 88 | |
| GLMCVenue=CVPR232026.05 | 87.8 | |
| ProCoBackbone=ResNet-32, Training Epochs=2002024.03 | 85.9 | |
| GLMC + SEL2026.05 | 85.4 | |
| FeatReconVenue=ICLR252026.05 | 85.2 | |
| ResComBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 84.9 | |
| RBLVenue=ICML232026.05 | 84.7 | |
| BCLBackbone=ResNet-32, Training Epochs=2002024.03 | 84.5 | |
| Logit AdjustmentBackbone=ResNet-32, Training Epochs=2002024.03 | 84.3 | |
| GCL + CRBackbone Net=ResNet-322023.03 | 83.5 | |
| GCLBackbone Net=ResNet-322023.03 | 82.7 | |
| ResLTBackbone=ResNet-32, Training Epochs=2002024.03 | 82.4 | |
| CE* + Lossreweighting=Inverse-view2026.05 | 82.3 | |
| MISLASBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 82.1 | |
| MISLASBackbone Net=ResNet-322023.03 | 82.1 | |
| MiSLASVenue=CVPR212026.05 | 82.1 | |
| CE* + Loss + LRreweighting=Inverse-view, LR Schedule=MiLeLR2026.05 | 82 | |
| CMO + Lossreweighting=Inverse-view2026.05 | 82 | |
| INC-DRWVenue=AISTATS232026.05 | 81.9 | |
| De-c-TDE + CRBackbone Net=ResNet-322023.03 | 81.8 | |
| RIDE-3 expertsVenue=ICLR212026.05 | 81.6 | |
| CMO + Loss + LRreweighting=Inverse-view, LR Schedule=MiLeLR2026.05 | 81.6 | |
| Balanced SoftmaxBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 81.5 | |
| FedYoYoVenue=ICCV252026.05 | 81.5 | |
| Hybrid-PSCBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 81.4 | |
| Hybrid-SCBackbone=ResNet-32, Training Epochs=2002024.03 | 81.4 | |
| HCLVenue=CVPR212026.05 | 81.4 | |
| BBN + CRBackbone Net=ResNet-322023.03 | 81.2 | |
| LDAM-DRWBackbone Net=ResNet-322023.03 | 81 | |
| MetaSAug-LDAMBackbone=ResNet-32, Training Epochs=2002024.03 | 80.7 | |
| Causal NormBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 80.6 | |
| Casual ModelBackbone=ResNet-32, Training Epochs=2002024.03 | 80.6 | |
| De-c-TDEBackbone Net=ResNet-322023.03 | 80.6 | |
| ResLTBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 80.5 | |
| BBNBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 79.9 | |
| BBNVenue=CVPR202026.05 | 79.9 | |
| BBNBackbone=ResNet-32, Training Epochs=2002024.03 | 79.8 | |
| BBNBackbone Net=ResNet-322023.03 | 79.8 | |
| TSCBackbone=ResNet-32, Training Epochs=2002024.03 | 79.7 | |
| TSCVenue=CVPR222026.05 | 79.7 | |
| RSGBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 79.5 | |
| ETF-DR + DisA2026.05 | 78.5 | |
| ELF+LDAMBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 78.1 | |
| ETF-DR + Lossreweighting=Inverse-view2026.05 | 77.9 | |
| ETF-DR + Loss + LRreweighting=Inverse-view, LR Schedule=MiLeLR2026.05 | 77.9 | |
| SSPBackbone=ResNet-32, Training Epochs=2002024.03 | 77.8 | |
| KCLVenue=ICLR212026.05 | 77.6 | |
| Focal-SAMVenue=ICML252026.05 | 77.2 | |
| LDAMBackbone=ResNet-32, Imbalanced Factor=1002022.03 | 77.1 | |
| LDAM-DRWBackbone=ResNet-32, Training Epochs=2002024.03 | 77 | |
| ETF-DRVenue=NeurIPS222026.05 | 76.5 | |
| IP-DPPVenue=NeurIPS252026.05 | 76.4 | |
| CE*reproduced=true2026.05 | 76 | |
| CB Loss + CRBackbone Net=ResNet-322023.03 | 75.8 | |
| SELVenue=ICCV252026.05 | 75.8 | |
| MLLM-LLaVA-FLType=Our framework2024.09 | 75.49 | |
| CMOVenue=CVPR22, reproduced=true2026.05 | 74.8 | |
| DisAVenue=ICML242026.05 | 74.7 | |
| CB-FocalBackbone=ResNet-32, Training Epochs=2002024.03 | 74.6 | |
| CB LossBackbone Net=ResNet-322023.03 | 74.5 | |
| CLIP2FLType=SOTA2024.09 | 73.37 | |
| Cross Entropy + CRBackbone Net=ResNet-322023.03 | 72.6 | |
| Focal Loss + CRBackbone Net=ResNet-322023.03 | 71.8 | |
| CReFFType=Classifier-retraining2024.09 | 70.55 | |
| Cross EntropyBackbone Net=ResNet-322023.03 | 70.3 | |
| Focal LossBackbone Net=ResNet-322023.03 | 70.3 | |
| CCVRType=Heterogeneity-oriented FL methods2024.09 | 69.53 | |
| Ratio LossType=Imbalance-oriented FL methods2024.09 | 59.75 | |
| FedNovaType=Heterogeneity-oriented FL methods2024.09 | 57.79 | |
| FedProxType=Heterogeneity-oriented FL methods2024.09 | 56.92 | |
| FedAvgType=Heterogeneity-oriented FL methods2024.09 | 56.17 | |
| FedBEType=Heterogeneity-oriented FL methods2024.09 | 55.79 | |
| FedDFType=Heterogeneity-oriented FL methods2024.09 | 55.15 | |
| Fed-Focal LossType=Imbalance-oriented FL methods2024.09 | 53.83 | |
| FedAvgMType=Heterogeneity-oriented FL methods2024.09 | 52.03 | |
| FedAvg+ τ-normType=Imbalance-oriented FL methods2024.09 | 49.95 |