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Federated Learning research benchmarks · SOTA2 Research

Federated Learning

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

2.17Time Consumption (s)

84

May 8, 2026

1.99Time Consumption (s)

84

May 8, 2026

Fashion-MNIST (val)

9Error Rate

80

May 1, 2026

Shakespeare (val)

3.721Perplexity

73

May 1, 2026

MNIST Severe Non-IID (Dirichlet α = 0.1)

4Communication Rounds

33

Feb 26, 2026

MNIST Severe Non-IID

24Communication Cost (MB)

33

Feb 26, 2026

50.611Accuracy

33

Feb 27, 2026

0.01Local Average Distance (AD)

30

Feb 26, 2026

99.7Jain's Fairness Index

21

Mar 13, 2026

0.997Jain's Fairness Index

21

Mar 13, 2026

CIFAR-100 500 clients, 1% participation Dirichlet 0.3 (train test)

31.74Accuracy (500 Rounds)

13

Feb 27, 2026

CIFAR-10 500 clients, 1% participation Dirichlet 0.3 (train test)

64.55Accuracy (500 Rounds)

13

Feb 27, 2026

Tiny-ImageNet (test)

31.47Accuracy (500R)

13

Feb 27, 2026

CIFAR-10 (test)

73.61Accuracy (500R)

13

Feb 27, 2026

CIFAR-100 100 clients Dirichlet 0.3

49.56Accuracy (500 Rounds)

13

Feb 27, 2026

CIFAR-10 100 clients Dirichlet 0.3

77.76Accuracy (Round 500)

13

Feb 27, 2026

79Mean F1 Score

12

Mar 19, 2026

89.2Mean F1 Score

12

Mar 19, 2026

80Mean F1 Score

12

Mar 19, 2026

86.2Mean F1 Score

12

Mar 19, 2026

0.01Local Avg Distance (AD)

12

Feb 26, 2026

EMNIST Cross-device

75.87Aθ Score

10

Apr 13, 2026

NASA Bearings Label Skew (downstream)

69.48Weighted Accuracy

10

Apr 10, 2026

18.86Speedup

10

Feb 26, 2026

Natural Instructions (NI)

48.8Speedup

10

Feb 26, 2026

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