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Benchmarks
Image Classification on Flowers (CA, BA)
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98.49
Accuracy (BA)
Attentive Probe
68.5484
76.3217
84.095
91.8683
Nov 15, 2022
May 26, 2023
Dec 5, 2023
Jun 15, 2024
Dec 24, 2024
Jul 5, 2025
Jan 14, 2026
Accuracy (BA)
Accuracy (CA)
Updated 3mo ago
Evaluation Results
Method
Method
Links
Accuracy (BA)
Accuracy (CA)
Attentive Probe
Layers=All, Tokens=CLS...
2026.01
98.49
-
AAT
Layers=Last, Tokens=al...
2026.01
98.44
-
Linear Probe
Layers=Last, Tokens=CL...
2026.01
98.43
-
Attentive Probe
Layers=Last, Tokens=CL...
2026.01
98.09
-
Linear Probe
Layers=Last, Tokens=CL...
2026.01
98.03
-
Linear Probe
Layers=All, Tokens=CLS...
2026.01
97.78
-
CLOP
Backbone=ResNet-50 (4x...
2025.11
97.18
-
SimCLR
Backbone=ResNet-50 (4x...
2025.11
97
-
FixMatch
Backbone=ResNet-50 (4x...
2025.11
96.69
-
SimMatch
Backbone=ResNet-50 (4x...
2025.11
96.46
-
SimMatch-V2
Backbone=ResNet-50 (4x...
2025.11
96.13
-
SupCon
Backbone=ResNet-50 (4x...
2025.11
96
-
SsCL
Backbone=ResNet-50 (4x...
2025.11
95.74
-
CCSSL
Backbone=ResNet-50 (4x...
2025.11
94.56
-
CorruptEncoder
Backbone=ResNet-18, CL...
2022.11
69.7
-
No Attack
Backbone=ResNet-18, CL...
2022.11
-
70.8
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