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Domain Adaptation research benchmarks – Page 5 · SOTA2 Research

Domain Adaptation

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

FFHQ to Amedeo Modigliani

Few-Shot Adaption

171.56FID

4

Feb 26, 2026

CIFAR10 to STL10 (test)

0Inference Time (sec/step)

4

Feb 26, 2026

Imbalanced USPS to MNIST (test)

99.9Accuracy

3

Feb 26, 2026

Imbalanced MNIST to USPS (test)

100Accuracy

3

Feb 26, 2026

MNIST (Target (mix of Group 1 and 2))

Bi-level ERM for Target Model Prediction

65Accuracy

3

Feb 26, 2026

MNIST (Target (Group 3))

Bi-level ERM for Target Model Prediction

55Accuracy

3

Feb 26, 2026

MNIST Target (Group 2)

Bi-level ERM for Target Model Prediction

69.9Accuracy

3

Feb 26, 2026

MNIST Target (Group 1)

Bi-level ERM for Target Model Prediction

80Accuracy

3

Feb 26, 2026

Office-Home (target)

50.45Accuracy (Art->Clipart)

3

Feb 26, 2026

Office-Home Rw -> Pr

LOLSGD + Ldistill + Lrank

82.95Overall Accuracy

3

Feb 26, 2026

Office-Home Rw -> Cl

LOLSGD + Ldistill + Lrank

65.71Overall Accuracy

3

Feb 26, 2026

Office-Home Rw -> Ar

LOLSGD + Ldistill + Lrank

70.13Overall Accuracy

3

Feb 26, 2026

Office-Home Ar -> Rw

LOLSGD + Ldistill + Lrank

76.7Overall Accuracy

3

Feb 26, 2026

Office-Home Source and Target

83.6Source Accuracy

3

Feb 26, 2026

Cat Domain Adaptation One-shot 1.0 (val)

13.13KID (Tiger)

3

Feb 26, 2026

AFHQ Cat to Wolf

44.39FID

3

Feb 26, 2026

AFHQ Cat to Fox

71.57FID

3

Feb 26, 2026

AFHQ Cat to Tiger

16.26FID

3

Feb 26, 2026

Office 15 labeled target classes 31 test classes

63.3Accuracy (A->W)

3

Feb 26, 2026

Caltech-office C/W (test)

83Accuracy (fi1)

3

Feb 26, 2026

Caltech-office C/D (test)

90Accuracy (fi1)

3

Feb 26, 2026

Caltech-office A/W (test)

79Acc (fi1)

3

Feb 26, 2026

Caltech-office A/D (test)

87Acc (fi1)

3

Feb 26, 2026

91.34Performance (L2 → L1)

2

Jun 25, 2026

RCC patch-level (Unbalanced)

94.4Balanced Accuracy

2

May 26, 2026

Page 5 of 6

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