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Image Classification on CIFAR-10 (test) (k-NN Accuracy)
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39.51
Test Accuracy (k=2)
UWA
20.9876
25.7963
30.605
35.4137
Sep 18, 2025
Test Accuracy (k=2)
Test Accuracy (k=3)
Test Accuracy (k=4)
Test Accuracy (k=5)
Test Accuracy (k=7)
Test Accuracy (k=9)
Reference Test Accuracy
Updated 2mo ago
Evaluation Results
Method
Method
Links
Test Accuracy (k=2)
Test Accuracy (k=3)
Test Accuracy (k=4)
Test Accuracy (k=5)
Test Accuracy (k=7)
Test Accuracy (k=9)
Reference Test Accuracy
UWA
Backbone=ResNet-18, Pr...
2025.09
39.51
59.37
64.71
68.96
71.23
73.16
80.84
sUWA
Backbone=ResNet-18, Pr...
2025.09
38.33
60.96
67.45
71.38
73.94
74.98
-
AVG
Backbone=ResNet-18, Pr...
2025.09
21.7
41.88
56.79
65.33
72.55
75.42
-
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