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ResearchFormerly WizWand

Image Classification on Tiny-ImageNet (Top-1 Accuracy)

90.6Top-1 AccuracyMTA
13.1233.23553.3573.465Mar 6, 2025May 6, 2025Jul 6, 2025Sep 5, 2025Nov 5, 2025Jan 5, 2026Mar 8, 2026
Updated 7mo ago

Evaluation results

MethodLinks
MTAMethod Category=Training-free TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1290.6
ZEROMethod Category=Training-free TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1290.6
C-TPTMethod Category=Prompt-based TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1290.5
PromptAlignMethod Category=Prompt-based TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1290
TDAMethod Category=Training-free TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1290
TPTMethod Category=Prompt-based TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1289.5
O-TPTMethod Category=Prompt-based TTA, Backbone=ViT-B/16, Pre-training=MaPLe2025.1289.3
CoOpMethod Category=Prompt Learning, Backbone=ViT-B/16, Pre-training=MaPLe2025.1289.2
MaPLeMethod Category=Prompt Learning, Backbone=ViT-B/16, Pre-training=MaPLe2025.1289
CLIPMethod Category=Pre-trained, Backbone=ViT-B/16, Pre-training=MaPLe2025.1287.6
DeepAFLalpha (α)=0.1, T (Number of layers)=202026.0262.35
DeepAFLalpha (α)=0.05, T (Number of layers)=202026.0262.35
DeepAFLalpha (α)=0.1, T (Number of layers)=102026.0261.37
DeepAFLalpha (α)=0.05, T (Number of layers)=102026.0261.37
DeepAFLalpha (α)=0.1, T (Number of layers)=52026.0260.31
DeepAFLalpha (α)=0.05, T (Number of layers)=52026.0260.31
FedAWAalpha (α)=0.12026.0259.07
D4M+EVLFIPC=502026.0358.5
RDEDIPC=502026.0358.2
D4MIPC=502026.0355.8
AFLalpha (α)=0.12026.0254.67
AFLalpha (α)=0.052026.0254.67
FedAWAalpha (α)=0.052026.0252.33
ViT-SOM-cls# Params=5.4M2025.0350.2
Swin-T# Params=27.5M2025.0350.1
FIPAData Distribution=alpha = 0.6, Performance Type=Max within 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0150.06
DeiT-T# Params=28.9M2025.0349.9
FIPAData Distribution=alpha = 0.6, Performance Type=Average over first 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0149.86
ViT-cls (reproduce)# Params=5.4M2025.0349.6
FedAvgData Distribution=alpha = 0.6, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0149.53
FedProxData Distribution=alpha = 0.6, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0149.53
FedRCLData Distribution=alpha = 0.6, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0149.35
D4M+EVLFIPC=102026.0349.2
FedProxData Distribution=alpha = 0.6, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0149.08
FedAvgData Distribution=alpha = 0.6, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0149.07
FedRCLData Distribution=alpha = 0.6, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0149.04
FIPAData Distribution=IID, Performance Type=Max within 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0149.03
FedProxData Distribution=IID, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0149
FedAvgData Distribution=IID, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0148.94
FIPAData Distribution=alpha = 0.3, Performance Type=Max within 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0148.94
FIPAData Distribution=IID, Performance Type=Average over first 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0148.92
FIPAData Distribution=alpha = 0.3, Performance Type=Average over first 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0148.76
FedRCLData Distribution=IID, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0148.72
FedProxData Distribution=IID, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0148.68
FedAvgData Distribution=IID, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0148.61
FedRCLData Distribution=IID, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0148.44
FedProxData Distribution=alpha = 0.3, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0148.1
FedRCLData Distribution=alpha = 0.3, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0148.1
FedAvgData Distribution=alpha = 0.3, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0148
FedProxData Distribution=alpha = 0.3, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0147.75
FedAvgData Distribution=alpha = 0.3, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0147.66
FedRCLData Distribution=alpha = 0.3, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0147.62
ResNet34# Params=21.8M2025.0346.8
FIPAData Distribution=alpha = 0.1, Performance Type=Max within 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0145.41
MobileViT-T# Params=4.9M2025.0345.2
FIPAData Distribution=alpha = 0.1, Performance Type=Average over first 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0144.73
FedProxData Distribution=alpha = 0.1, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0143.9
FedAvgData Distribution=alpha = 0.1, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0143.68
FedRCLData Distribution=alpha = 0.1, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0143.55
FedProxData Distribution=alpha = 0.1, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0143.23
FedRCLData Distribution=alpha = 0.1, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0143.03
FedAvgData Distribution=alpha = 0.1, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0142.99
D4MIPC=102026.0342.5
RDEDIPC=102026.0341.9
SRe2LIPC=502026.0341.1
FIPAData Distribution=alpha = 0.05, Performance Type=Max within 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0139.86
FedLPAalpha (α)=0.12026.0239.48
FIPAData Distribution=alpha = 0.05, Performance Type=Average over first 100 rounds, Backbone=ResNet-18, Updated Layers=FC layers only2026.0138.74
FedRCLData Distribution=alpha = 0.05, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0137.5
FedProxData Distribution=alpha = 0.05, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0137.47
FedAvgData Distribution=alpha = 0.05, Performance Type=Max within 100 rounds, Backbone=ResNet-182026.0137.38
FedProxData Distribution=alpha = 0.05, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0136.85
FedAvgData Distribution=alpha = 0.05, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0136.67
FedRCLData Distribution=alpha = 0.05, Performance Type=Average over first 100 rounds, Backbone=ResNet-182026.0136.61
FedLPAalpha (α)=0.052026.0226.67
SRe2LIPC=102026.0316.1