Image Classification on SVHN (Standard Accuracy)
98.6AccuracyNoisy Student Training
Evaluation Results
| Method | Links | |
|---|---|---|
| Noisy Student TrainingBackbone=B02019.11 | 98.6 | |
| RandAugmentBackbone=WRN2019.11 | 98.3 | |
| RoPEPositional Encoding=RoPE2026.03 | 98.15 | |
| PaRaMSModel Status=Protected Standalone (θ̂_def)2025.11 | 98.11 | |
| RandAugmentBackbone=EfficientNet-B02019.11 | 98.1 | |
| No PEPositional Encoding=None2026.03 | 98.09 | |
| Learnable PEPositional Encoding=Learnable2026.03 | 98.09 | |
| ResNet-18Backbone=ResNet-182026.03 | 97.98 | |
| AdapterTuneBackbone=ViT-B/16, Trainable Parameters (%)=0.9%2026.03 | 97.5 | |
| Full fine-tuningBackbone=ViT-B/16, Trainable Parameters (%)=100%2026.03 | 97.5 | |
| Full fine-tuningBackbone=ViT-S/16, Trainable Parameters (%)=100%2026.03 | 97.4 | |
| Full fine-tuningBackbone=DeiT-T, Trainable Parameters (%)=100%2026.03 | 97.2 | |
| MergeGuardModel Status=Protected Standalone (θ̂_def)2025.11 | 96.82 | |
| Fine-TunedBackbone=CLIP ViT-B/32, Classes=102025.12 | 96.4 | |
| AdapterTuneBackbone=ViT-S/16, Trainable Parameters (%)=0.9%2026.03 | 96.2 | |
| AdapterTuneBackbone=DeiT-T, Trainable Parameters (%)=0.9%2026.03 | 95.3 | |
| ADAProtection Status=None (theta_merge)2025.11 | 93.4 | |
| TIESProtection Status=None (theta_merge)2025.11 | 90.3 | |
| M-TIESBackbone=ViT-L/142026.02 | 89.78 | |
| TIESBackbone=ViT-L/142026.02 | 89.42 | |
| DAREBackbone=ViT-L/142026.02 | 89.19 | |
| TAProtection Status=None (theta_merge)2025.11 | 87.9 | |
| TIESBackbone=ViT-B/322026.02 | 86.2 | |
| Task ArithmeticBackbone=ViT-L/142026.02 | 85.26 | |
| EnsemblingBackbone=ViT-L/142026.02 | 84.92 | |
| DAREBackbone=ViT-B/322026.02 | 83.96 | |
| M-TIESBackbone=ViT-B/322026.02 | 83.06 | |
| EnsemblingBackbone=ViT-B/322026.02 | 82.15 | |
| Simple Avg.Backbone=ViT-L/142026.02 | 78.23 | |
| WAProtection Status=None (theta_merge)2025.11 | 78.2 | |
| Task ArithmeticBackbone=ViT-B/322026.02 | 76.68 | |
| PaRaMSModel Status=Merged (θ̂_merge)2025.11 | 71.95 | |
| M-CovJac#p/n=4, L=6, k=128k, iterations=50k, τ=1.02026.05 | 68.91 | |
| Soft-Mix#p/n=16, L=6, k=128k, iterations=50k, τ=1.02026.05 | 68.21 | |
| Task MatrixBackbone=CLIP ViT-B/32, Best Layer=8, Classes=102025.12 | 66.7 | |
| M-STE#p/n=4, L=6, k=128k, iterations=50k, τ=1.02026.05 | 66.69 | |
| Linear ProbeBackbone=CLIP ViT-B/32, Classes=102025.12 | 66.6 | |
| Gumbel-ST#p/n=16, L=6, k=128k, iterations=50k, τ=1.02026.05 | 66.12 | |
| Head-only tuningBackbone=ViT-B/16, Trainable Parameters (%)=0.1%2026.03 | 65.5 | |
| Simple Avg.Backbone=ViT-B/322026.02 | 64.16 | |
| Head-only tuningBackbone=ViT-S/16, Trainable Parameters (%)=0.1%2026.03 | 54.5 | |
| TAProtection Status=With MergeGuard (theta_hat_merge)2025.11 | 47.28 | |
| MergeGuardModel Status=Merged (θ̂_merge)2025.11 | 47.28 | |
| Head-only tuningBackbone=DeiT-T, Trainable Parameters (%)=0.1%2026.03 | 44.5 | |
| WAProtection Status=With MergeGuard (theta_hat_merge)2025.11 | 10.05 | |
| TIESProtection Status=With MergeGuard (theta_hat_merge)2025.11 | 7.77 | |
| ADAProtection Status=With MergeGuard (theta_hat_merge)2025.11 | 7.76 |