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Federated Learning research benchmarks – Page 2 · SOTA2 Research

Federated Learning

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

CIFAR-10 standard

101Rounds (Acc 20%)

9

Feb 27, 2026

DomainNet (test)

55Clipart Score

9

Feb 26, 2026

Full Fine-tuning

85.8Test Accuracy

8

Feb 26, 2026

AV-MNIST alpha=0.1 (test)

97.73Accuracy (%)

7

Jul 9, 2026

0.88Communication (MB/round)

7

Jul 9, 2026

0.56Accuracy

7

Jul 1, 2026

62.4Accuracy

7

Jul 1, 2026

78.91Accuracy

7

Jul 1, 2026

95.8Jain's Fairness Index

7

Mar 13, 2026

99.9Jain's Fairness Index

7

Mar 13, 2026

CIFAR-10 (train)

9.82Time per Round (s)

7

Feb 26, 2026

CIFAR-100 dynamic client updates (Dirichlet 0.3)

32.7Accuracy (500R)

7

Feb 27, 2026

CIFAR-10 LS K=3

0.08Gini Coefficient

6

May 25, 2026

CIFAR-10 LS K=2

0.071Gini Coefficient

6

May 25, 2026

CIFAR-10 LS K=1

0.073Gini Coefficient

6

May 25, 2026

CIFAR-10 Dir 0.1

0.125Gini Coefficient

6

May 25, 2026

CIFAR-10 Dir 0.5

0.062Gini Coefficient

6

May 25, 2026

CIFAR-10 (Dir 0.8)

2.45Gini Coefficient

6

May 25, 2026

0.011Gini Coefficient

6

May 25, 2026

Single-Job Federated Learning (Non-IID)

98.4Accuracy

6

May 4, 2026

Single-Job Federated Learning (IID)

99.33Accuracy

6

May 4, 2026

NASA Bearings Corrupted Client (downstream)

Single-Shot LLM

62.65Weighted Accuracy

5

Apr 10, 2026

NASA Bearings Feature Skew (downstream)

72.5Weighted Accuracy

5

Apr 10, 2026

NASA Bearings Label Poisoning (downstream)

62.23Weighted Accuracy

5

Apr 10, 2026

0.031Latency (s)

5

Feb 26, 2026

Page 2 of 3

Popular datasets

CIFAR MNIST NASA Bearings CIFAR-100 DomainNet

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