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Models/VS + ADRW + TLA

VS + ADRW + TLA

Reported on 20 benchmarks across 5 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology12 results

Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2023-10-07
8.18
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-10-07
34.41
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-10-07
46.95
best: 10.9 (LPT)
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2023-10-07
13.58
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Long-tail LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2023-10-07
8.18
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-10-07
34.41
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-10-07
46.95
best: 10.9 (LPT)
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Long-tail LearningonCIFAR-10-LT (ρ=100)
Error Rate· 2023-10-07
13.58
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2023-10-07
8.18
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-10-07
34.41
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-10-07
46.95
best: 10.9 (LPT)
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=100)
Error Rate· 2023-10-07
13.58
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752

Computer Vision8 results

Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2023-10-07
8.18
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-10-07
34.41
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-10-07
46.95
best: 10.9 (LPT)
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2023-10-07
13.58
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2023-10-07
8.18
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-10-07
34.41
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-10-07
46.95
best: 10.9 (LPT)
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2023-10-07
13.58
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning arXiv:2310.04752