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Models/GCE

GCE

Reported on 14 benchmarks across 3 tasks · 2 papers · 1 SOTA

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)· 2018-05-20
87.7
best: 96.21 (PSSCL)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Image ClassificationonCIFAR-10N-Random3
Accuracy (mean)· 2018-05-20
87.58
best: 96.49 (PSSCL)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Image ClassificationonCIFAR-10N-Aggregate
Accuracy (mean)· 2018-05-20
87.85
best: 97.39 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Image ClassificationonCIFAR-10N-Random1
Accuracy (mean)· 2018-05-20
87.61
best: 96.97 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Image ClassificationonCIFAR-100N
Accuracy (mean)· 2018-05-20
56.73
best: 74.08 (PGDF)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Image ClassificationonCIFAR-10N-Worst
Accuracy (mean)· 2018-05-20
80.66
best: 96.16 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836

Medical6 results

Document Text ClassificationonCIFAR-10N-Random2
Accuracy (mean)· 2018-05-20
87.7
best: 96.21 (PSSCL)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Document Text ClassificationonCIFAR-10N-Random3
Accuracy (mean)· 2018-05-20
87.58
best: 96.49 (PSSCL)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Document Text ClassificationonCIFAR-10N-Aggregate
Accuracy (mean)· 2018-05-20
87.85
best: 97.39 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Document Text ClassificationonCIFAR-10N-Random1
Accuracy (mean)· 2018-05-20
87.61
best: 96.97 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Document Text ClassificationonCIFAR-100N
Accuracy (mean)· 2018-05-20
56.73
best: 74.08 (PGDF)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836
Document Text ClassificationonCIFAR-10N-Worst
Accuracy (mean)· 2018-05-20
80.66
best: 96.16 (ProMix)
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels arXiv:1805.07836

Speech2 results

DialogueonWizard-of-Oz
Request· 2018-12-03
97.4
best: 97.6 (BERT-based tracker)
SOTA
Toward Scalable Neural Dialogue State Tracking Model arXiv:1812.00899
DialogueonWizard-of-Oz
Joint· 2018-12-03
88.5
best: 91.37 (AG-DST)
Toward Scalable Neural Dialogue State Tracking Model arXiv:1812.00899