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Models/T-Revision

T-Revision

Reported on 12 benchmarks across 2 tasks · 1 paper

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

Computer Vision6 results

  • Image ClassificationonCIFAR-10N-Random2
    Accuracy (mean)· 2019-06-01
    87.71
    best: 96.21 (PSSCL)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Image ClassificationonCIFAR-10N-Random3
    Accuracy (mean)· 2019-06-01
    87.79
    best: 96.49 (PSSCL)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Image ClassificationonCIFAR-10N-Aggregate
    Accuracy (mean)· 2019-06-01
    88.52
    best: 97.39 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Image ClassificationonCIFAR-10N-Random1
    Accuracy (mean)· 2019-06-01
    88.33
    best: 96.97 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Image ClassificationonCIFAR-100N
    Accuracy (mean)· 2019-06-01
    51.55
    best: 74.08 (PGDF)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Image ClassificationonCIFAR-10N-Worst
    Accuracy (mean)· 2019-06-01
    80.48
    best: 96.16 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189

Medical6 results

  • Document Text ClassificationonCIFAR-10N-Random2
    Accuracy (mean)· 2019-06-01
    87.71
    best: 96.21 (PSSCL)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Document Text ClassificationonCIFAR-10N-Random3
    Accuracy (mean)· 2019-06-01
    87.79
    best: 96.49 (PSSCL)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Document Text ClassificationonCIFAR-10N-Aggregate
    Accuracy (mean)· 2019-06-01
    88.52
    best: 97.39 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Document Text ClassificationonCIFAR-10N-Random1
    Accuracy (mean)· 2019-06-01
    88.33
    best: 96.97 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Document Text ClassificationonCIFAR-100N
    Accuracy (mean)· 2019-06-01
    51.55
    best: 74.08 (PGDF)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189
  • Document Text ClassificationonCIFAR-10N-Worst
    Accuracy (mean)· 2019-06-01
    80.48
    best: 96.16 (ProMix)
    Are Anchor Points Really Indispensable in Label-Noise Learning?arXiv:1906.00189