# Image Classification on CIFAR-10 (test) (Clean Accuracy and CRA Robustness)

Source: [Image Classification on CIFAR-10 (test) (Clean Accuracy and CRA Robustness)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-clean-accuracy-and-cra-robustness>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:39:18.532Z

Evaluation of Image Classification performance on the CIFAR-10 test set, focusing on standard Clean Accuracy and Corruption Robustness Accuracy (CRA) measured under varying levels of input corruption (noise levels 36/255, 72/255, and 108/255).

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Image Classification |
| Dataset (including any stated split) | CIFAR-10 (test) |
| Metric | Clean Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 10 of 10 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Clean Accuracy](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-clean-accuracy-and-cra-robustness.md?metric=Clean%20Accuracy>): Higher is better; unit: PERCENT.

- [CRA (Noise 36/255)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-clean-accuracy-and-cra-robustness.md?metric=CRA%20(Noise%2036%2F255)>): Higher is better; unit: PERCENT.

- [CRA (Noise 72/255)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-clean-accuracy-and-cra-robustness.md?metric=CRA%20(Noise%2072%2F255)>): Higher is better; unit: PERCENT.

- [CRA (Noise 108/255)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-clean-accuracy-and-cra-robustness.md?metric=CRA%20(Noise%20108%2F255)>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Clean Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| LipNeXt L32W2048 | 85 | Not recorded | 697846dfa2b28e761d87c821 |
| BRONet | 81.6 | Not recorded | 697846dfa2b28e761d87c821 |
| LipNeXt L32W1024 | 81.5 | Not recorded | 697846dfa2b28e761d87c821 |
| LiResNet | 81 | Not recorded | 697846dfa2b28e761d87c821 |
| CPL XL | 78.5 | Not recorded | 697846dfa2b28e761d87c821 |
| LOT-20 | 77.1 | Not recorded | 697846dfa2b28e761d87c821 |
| SOC-20 | 76.3 | Not recorded | 697846dfa2b28e761d87c821 |
| Cayley Large | 74.6 | Not recorded | 697846dfa2b28e761d87c821 |
| SLL X-Large | 73.3 | Not recorded | 697846dfa2b28e761d87c821 |
| AOL Large | 71.6 | Not recorded | 697846dfa2b28e761d87c821 |

### LipNeXt L32W2048

Clean Accuracy: 85. Result ID: 6999158b5698665ec47bae75.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

Recorded evaluation configuration: {"#Param.":"256M"}. This record does not assert independent reproduction.

### BRONet

Clean Accuracy: 81.6. Result ID: 6999158b5698665ec47bae73.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7a611e209131cea82bb3.md>)

Recorded evaluation configuration: {"#Param.":"68M"}. This record does not assert independent reproduction.

### LipNeXt L32W1024

Clean Accuracy: 81.5. Result ID: 6999158b5698665ec47bae74.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

Recorded evaluation configuration: {"#Param.":"64M"}. This record does not assert independent reproduction.

### LiResNet

Clean Accuracy: 81. Result ID: 6999158b5698665ec47bae72.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa73b61e209131cea5e0f9.md>)

Recorded evaluation configuration: {"#Param.":"83M"}. This record does not assert independent reproduction.

### CPL XL

Clean Accuracy: 78.5. Result ID: 6999158b5698665ec47bae6f.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6bb31e209131cea2fa63.md>)

Recorded evaluation configuration: {"#Param.":"236M"}. This record does not assert independent reproduction.

### LOT-20

Clean Accuracy: 77.1. Result ID: 6999158b5698665ec47bae6e.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6ee71e209131cea42cbd.md>)

[Implementation](<https://github.com/AI-secure/Layerwise-Orthogonal-Training>)

Recorded evaluation configuration: {"#Param.":"18M"}. This record does not assert independent reproduction.

### SOC-20

Clean Accuracy: 76.3. Result ID: 6999158b5698665ec47bae6d.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6a291e209131cea2676b.md>)

Recorded evaluation configuration: {"#Param.":"27M"}. This record does not assert independent reproduction.

### Cayley Large

Clean Accuracy: 74.6. Result ID: 6999158b5698665ec47bae6c.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69cb1e209131cea24142.md>)

Recorded evaluation configuration: {"#Param.":"21M"}. This record does not assert independent reproduction.

### SLL X-Large

Clean Accuracy: 73.3. Result ID: 6999158b5698665ec47bae71.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa71091e209131cea4ecb1.md>)

[Implementation](<https://www.sota2.com/github.com/araujoalexandre/Lipschitz-SLL-Networks>)

Recorded evaluation configuration: {"#Param.":"236M"}. This record does not assert independent reproduction.

### AOL Large

Clean Accuracy: 71.6. Result ID: 6999158b5698665ec47bae70.

[Reporting paper](<https://www.sota2.com/research/paper/697846dfa2b28e761d87c821.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa70731e209131cea4b18d.md>)

Recorded evaluation configuration: {"#Param.":"136M"}. This record does not assert independent reproduction.

Page 1 of 1. This is an index page, not the full collection.
