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Models/KCL

KCL

Reported on 10 benchmarks across 5 tasks

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

Methodology6 results

  • Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=10)
    Error Rate
    12
    best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
  • Generalized Few-Shot ClassificationonImageNet-LT
    Top-1 Accuracy
    51.5
    best: 82.9 (LIFT (ViT-L/14))
  • Long-tail LearningonCIFAR-10-LT (ρ=10)
    Error Rate
    12
    best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
  • Long-tail LearningonImageNet-LT
    Top-1 Accuracy
    51.5
    best: 82.9 (LIFT (ViT-L/14))
  • Generalized Few-Shot LearningonCIFAR-10-LT (ρ=10)
    Error Rate
    12
    best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
  • Generalized Few-Shot LearningonImageNet-LT
    Top-1 Accuracy
    51.5
    best: 82.9 (LIFT (ViT-L/14))

Computer Vision4 results

  • Image ClassificationonCIFAR-10-LT (ρ=10)
    Error Rate
    12
    best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
  • Image ClassificationonImageNet-LT
    Top-1 Accuracy
    51.5
    best: 82.9 (LIFT (ViT-L/14))
  • Few-Shot Image ClassificationonCIFAR-10-LT (ρ=10)
    Error Rate
    12
    best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
  • Few-Shot Image ClassificationonImageNet-LT
    Top-1 Accuracy
    51.5
    best: 82.9 (LIFT (ViT-L/14))