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Top-1 Accuracy on ImageNet-1K (val)

64.69Top-1 AccuracyTDDS
9.580423.887738.19552.5023Nov 22, 2023Mar 17, 2024Jul 11, 2024Nov 5, 2024Mar 1, 2025Jun 25, 2025Oct 20, 2025
Updated 7mo ago

Evaluation results

MethodLinks
TDDSPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1164.69
ForgettingPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1164.29
RandomPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1164.19
ModeratePruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1164.04
DAPIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1062.7
TDDSPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1162.56
EntropyPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1162.34
ForgettingPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1162.01
ModeratePruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1161.35
RandomPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1160.76
VLCPIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1060.5
MGD3IPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1060.2
IGDIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1059.8
D3HRIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1059.4
MinimaxIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1058.6
EntropyPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1156.8
RDEDIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1056.5
TDDSPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1153.91
DiTIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1052.9
RandomPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1152.63
ModeratePruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1152.45
ForgettingPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1152.14
G-VBSMIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1051.8
DAPIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1049.1
EL2NPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1146.92
SRe2LIPC=50, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1046.8
VLCPIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1046.7
MGD3IPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1045.6
IGDIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1045.5
MinimaxIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1044.3
D3HRIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1044.3
EntropyPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1143.39
RDEDIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1042
DiTIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1039.6
AUMPruning Rate (p)=70%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1139.34
EL2NPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1132.68
G-VBSMIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1031.4
AUMPruning Rate (p)=80%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1123.64
SRe2LIPC=10, Evaluation Protocol=soft-label, Model Architecture=ResNet-182025.1021.3
EL2NPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1115.9
AUMPruning Rate (p)=90%, Backbone=ResNet-34, Training Strategy=Strategy-E2023.1111.7