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Machine Unlearning research benchmarks – Page 11 · SOTA2 Research

Machine Unlearning

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Office-31 D → A (test)

78.6Retained Performance D->A

11

Apr 10, 2026

Office-31 A → W (test)

87Accuracy (r)

11

Apr 10, 2026

Office-31 A → D (test)

77.2Accuracy (A->D, r)

11

Apr 10, 2026

85.52RA

11

Mar 10, 2026

ImageNet (test)

81.06Atest Score

11

Mar 10, 2026

ImageNet Forget set

98.02Au

11

Mar 10, 2026

Fashion-MNIST 2% (test)

86.56Accuracy

11

Feb 26, 2026

Fashion-MNIST 2% subset

0.942Accuracy

11

Feb 26, 2026

Iris 2% (forgotten)

0.312UQI

11

Feb 26, 2026

Iris subset 2% (test)

100Accuracy

11

Feb 26, 2026

Iris subset 2% (retained)

94Accuracy

11

Feb 26, 2026

CIFAR-100 Random Forget (40%)

96.96FA

11

Feb 26, 2026

CIFAR-100 Random Forget 30% (forget set)

97.02FA (%)

11

Feb 26, 2026

CIFAR-100 Random Forget (forget set 20%)

97.02FA

11

Feb 26, 2026

Tiny-Imagenet Random Forget 10%, γ=1 (test)

96.33FA

11

Feb 26, 2026

Tiny-Imagenet Random Forget 30%, γ=1/3 (test)

95.85FA

11

Feb 26, 2026

Tiny-Imagenet Random Forget 20%, γ=0 (test)

95.68FA

11

Feb 26, 2026

TOFU Llama 3.1 8B (10%)

0.671Forgetting Quality

11

Feb 26, 2026

CIFAR-10 single-class forgetting

90.5Accuracy F

11

Feb 27, 2026

81.46AUC

10

Jun 30, 2026

73.38Accuracy

10

Jun 30, 2026

SkinCancer (unlearning set Du)

93.23Agreement

10

Jun 16, 2026

86.84Accuracy

10

May 27, 2026

81.67Accuracy

10

May 27, 2026

ImageNet-100 (test)

25.77UA

10

May 13, 2026

Page 11 of 22

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