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Models/SemiOccam

SemiOccam

Reported on 10 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Computer Vision10 results

  • Image ClassificationonCIFAR-100, 2500 Labels
    Percentage error· 2025-06-04
    22.19
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Image ClassificationonSTL-10, 40 Labels
    Accuracy· 2025-06-04
    95.43
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Image ClassificationonCIFAR-10, 40 Labels
    Percentage error· 2025-06-04
    3.51
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Image ClassificationonCIFAR-10, 250 Labels
    Percentage error· 2025-06-04
    3.47
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Semi-Supervised Image ClassificationonCIFAR-100, 2500 Labels
    Percentage error· 2025-06-04
    22.19
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Semi-Supervised Image ClassificationonSTL-10, 40 Labels
    Accuracy· 2025-06-04
    95.43
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Semi-Supervised Image ClassificationonCIFAR-10, 40 Labels
    Percentage error· 2025-06-04
    3.51
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Semi-Supervised Image ClassificationonCIFAR-10, 250 Labels
    Percentage error· 2025-06-04
    3.47
    SOTA
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Image ClassificationonCIFAR-100, 400 Labels
    Percentage error· 2025-06-04
    26.59
    best: 15.62 (SemiReward)
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582
  • Semi-Supervised Image ClassificationonCIFAR-100, 400 Labels
    Percentage error· 2025-06-04
    26.59
    best: 15.62 (SemiReward)
    ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse LabelsarXiv:2506.03582