| image-classification-on-clothing1m | Super-SST (ViT-Small, 5% Labels) | – | Accuracy: 75.7% |
| image-classification-on-food-101 | Semi-SST (ViT-Base, 1% Labels) | – | Accuracy (%): 86.5 |
| image-classification-on-food-101 | Semi-SST (ViT-Base, 10% Labels) | – | Accuracy (%): 91.5 |
| image-classification-on-food-101 | Super-SST (ViT-Base, 1% Labels) | – | Accuracy (%): 83.4 |
| image-classification-on-food-101 | Super-SST (ViT-Base, 10% Labels) | – | Accuracy (%): 91.1 |
| semi-supervised-image-classification-on-cifar-10-250-labels | Semi-SST (ViT-Small) | – | Percentage error: 2.42±0.13 |
| semi-supervised-image-classification-on-cifar-10-250-labels | Super-SST (ViT-Small) | – | Percentage error: 3.37±0.22 |
| semi-supervised-image-classification-on-cifar-10-40-labels | Semi-SST (ViT-Small) | – | Percentage error: 6.35±0.28 |
| semi-supervised-image-classification-on-cifar-10-40-labels | Super-SST (ViT-Small) | – | Percentage error: 9.59 |
| semi-supervised-image-classification-on-cifar-10-4000-labels | Semi-SST (ViT-Small) | – | Percentage error: 1.41±0.10 |
| semi-supervised-image-classification-on-cifar-10-4000-labels | Super-SST (ViT-Small) | – | Percentage error: 1.61±0.18 |
| semi-supervised-image-classification-on-cifar-100-10000-labels | Semi-SST (ViT-Small) | – | Percentage error: 13.50±0.14 |
| semi-supervised-image-classification-on-cifar-100-10000-labels | Super-SST (ViT-Small) | – | Percentage error: 14.20±0.17 |
| semi-supervised-image-classification-on-cifar-100-2500-labels | Semi-SST (ViT-Small) | – | Percentage error: 16.62±0.28 |
| semi-supervised-image-classification-on-cifar-100-2500-labels | Super-SST (ViT-Small) | – | Percentage error: 18.51±0.36 |
| semi-supervised-image-classification-on-cifar-100-400-labels | Semi-SST (ViT-Small) | – | Percentage error: 31.39±0.47 |
| semi-supervised-image-classification-on-cifar-100-400-labels | Super-SST (ViT-Small) | – | Percentage error: 35.50±0.58 |
| semi-supervised-image-classification-on-imagenet-1-labeled-data | Semi-SST (ViT-Huge) | – | Top 1 Accuracy: 80.7% |
| semi-supervised-image-classification-on-imagenet-1-labeled-data | Semi-SST (ViT-Small) | – | Top 1 Accuracy: 71.4% |
| semi-supervised-image-classification-on-imagenet-1-labeled-data | Super-SST (ViT-Huge) | – | Top 1 Accuracy: 80.3% |
| semi-supervised-image-classification-on-imagenet-1-labeled-data | Super-SST (ViT-Small distilled) | – | Top 1 Accuracy: 76.9% |
| semi-supervised-image-classification-on-imagenet-1-labeled-data | Super-SST (ViT-Small) | – | Top 1 Accuracy: 70.4% |
| semi-supervised-image-classification-on-imagenet-10-labeled-data | Semi-SST (ViT-Huge) | – | Top 1 Accuracy: 84.9% |
| semi-supervised-image-classification-on-imagenet-10-labeled-data | Semi-SST (ViT-Small) | – | Top 1 Accuracy: 78.6% |
| semi-supervised-image-classification-on-imagenet-10-labeled-data | Super-SST (ViT-Huge) | – | Top 1 Accuracy: 84.8% |
| semi-supervised-image-classification-on-imagenet-10-labeled-data | Super-SST (ViT-Small distilled) | – | Top 1 Accuracy: 80.3% |
| semi-supervised-image-classification-on-imagenet-10-labeled-data | Super-SST (ViT-Small) | – | Top 1 Accuracy: 78.3% |
| semi-supervised-image-classification-on-stl-10-1000-labels | Semi-SST (ViT-Small) | – | Accuracy: 98.64±0.08 |
| semi-supervised-image-classification-on-stl-10-1000-labels | Super-SST (ViT-Small) | – | Accuracy: 98.55±0.10 |