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ResearchFormerly WizWand

Image Classification on ImageNet-1K (val) (Efficiency Deltas)

0Top-1 Accuracy Delta (pp)GTP-15.3
-1.12326.458414.0421.6216Sep 29, 2025
Updated 4mo ago

Evaluation results

MethodLinks
GTP-15.3Backbone=DeiT-B/162025.09013.070
BALF-P-0.8Backbone=DeiT-B/162025.090.1719.3619.94
BALF-F-0.8Backbone=DeiT-B/162025.090.1919.2219.79
BALF-P-0.9Backbone=MobileNetV22025.090.230.1210.69
DC-ViTBackbone=DeiT-B/162025.090.5416.6—
BALF-P-0.8Backbone=MobileNetV22025.090.610.2319.8
BALF-P-0.8Backbone=ResNet-502025.091.119.0321.9
BALF-F-0.7Backbone=DeiT-B/162025.091.2528.7829.64
BALF-P-0.7Backbone=DeiT-B/162025.091.3429.0429.91
IFMBackbone=ResNet-50, Setting=Row 12025.091.46—5.65
BALF-P-0.8Backbone=ResNet-18, Objective=Parameter count objective2025.091.696.7722.28
BALF-F-0.8Backbone=ResNet-502025.091.6920.039.73
CP-ALS-SBackbone=ResNet-18, Setting=High parameters2025.091.91—51.69
BALF-P-0.7Backbone=ResNet-502025.091.9713.629.95
PRACTISEBackbone=DeiT-B/162025.092.516.6—
T-ALS-SBackbone=ResNet-50, Setting=Row 12025.092.57—27.54
T-ALS-SBackbone=ResNet-18, Setting=High parameters2025.093—28.57
ITVSPBackbone=ResNet-50, Setting=Row 12025.093.02—4.76
BALF-P-0.7Backbone=ResNet-18, Objective=Parameter count objective2025.093.29.1329.99
CP-ALSBackbone=ResNet-18, Setting=High parameters2025.093.22—51.69
BALF-F-0.7Backbone=ResNet-502025.093.530.0121.66
GTP-8.8Backbone=DeiT-B/162025.093.5500
BALF-F-0.6Backbone=DeiT-B/162025.094.138.3739.52
BALF-P-0.6Backbone=DeiT-B/162025.094.3138.7139.87
L2+RESTBackbone=MobileNetV2, Setting=Low parameters2025.094.42—5
T-ALSBackbone=ResNet-50, Setting=Row 12025.094.49—27.54
BALF-F-0.97Backbone=MobileNetV22025.094.892.511.55
BALF-F-0.8Backbone=ResNet-18, Objective=FLOP objective2025.095.4920.0116.74
DFPCBackbone=ResNet-50, Setting=Row 12025.095.78—5.66
BALF-P-0.75Backbone=MobileNetV22025.096.171.1324.78
T-ALS-SBackbone=ResNet-18, Setting=Low parameters2025.096.5—43.5
CP-ALS-SBackbone=ResNet-18, Setting=Low parameters2025.096.7—69.23
T-ALS-SBackbone=ResNet-50, Setting=Row 22025.096.9—33.33
BALF-P-0.6Backbone=ResNet-18, Objective=Parameter count objective2025.09713.2640.01
BALF-P-0.5Backbone=ResNet-502025.097.7928.1750.06
CP-ALSBackbone=ResNet-18, Setting=Low parameters2025.098.03—60.47
BALF-F-0.7Backbone=ResNet-18, Objective=FLOP objective2025.098.530.7128.68
ITVSPBackbone=ResNet-50, Setting=Row 22025.0910.21—9.98
IFMBackbone=ResNet-50, Setting=Row 22025.0910.45—20.42
T-ALSBackbone=ResNet-18, Setting=High parameters2025.0910.9—28.57
SVD-NASBackbone=MobileNetV22025.0912.5415.099
SVD-NASBackbone=ResNet-182025.0913.3558.668.05
DFPCBackbone=ResNet-50, Setting=Row 22025.0913.88—10.92
BALF-F-0.5Backbone=ResNet-502025.0913.9650.0343.84
BALF-F-0.6Backbone=ResNet-18, Objective=FLOP objective2025.0915.2541.1839.45
ALDSBackbone=MobileNetV22025.0916.952.6237.61
LR-S2Backbone=MobileNetV22025.0917.463.816.24
T-ALSBackbone=ResNet-18, Setting=Low parameters2025.0917.6—33.33
L2+RESTBackbone=MobileNetV2, Setting=High parameters2025.0918.47—10
ALDSBackbone=ResNet-182025.0918.742.3165.14
T-ALSBackbone=ResNet-50, Setting=Row 22025.0920.14—33.33
BALF-P-0.7Backbone=MobileNetV22025.0928.082.0729.72