# Image Classification on CIFAR-10 (test) (Type I, II, III 70%)

Source: [Image Classification on CIFAR-10 (test) (Type I, II, III 70%)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-type-i-ii-iii-70-percent>)

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

Data updated: 2026-02-26T06:07:45.883Z

Evaluation of Image Classification model performance on the CIFAR-10 test set, reporting results across Type-I, Type-II, and Type-III metrics, all measured at a 70% threshold or level.

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 | Type-I 70% Score |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 6 of 6 |
| 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

- [Type-I 70% Score](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-type-i-ii-iii-70-percent.md?metric=Type-I%2070%25%20Score>): Higher is better; unit: PERCENT.

- [Type-II 70% Score](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-type-i-ii-iii-70-percent.md?metric=Type-II%2070%25%20Score>): Higher is better; unit: PERCENT.

- [Type-III 70% Score](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-test-type-i-ii-iii-70-percent.md?metric=Type-III%2070%25%20Score>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Type-I 70% Score | Result date | Report paper |
| --- | --- | --- | --- |
| PLC | 42.74 | Not recorded | 68fa6dad1e209131cea3b71c |
| Cross-Entropy | 41.98 | Not recorded | 68fa6dad1e209131cea3b71c |
| Bootstrapping Training Algorithm | 21.17 | Not recorded | 68fa6dad1e209131cea3b71c |
| Bootstrapping Training Algorithm | 21.02 | Not recorded | 68fa6dad1e209131cea3b71c |
| Bootstrapping Training Algorithm | 19.71 | Not recorded | 68fa6dad1e209131cea3b71c |
| Bootstrapping Training Algorithm | 19.18 | Not recorded | 68fa6dad1e209131cea3b71c |

### PLC

Type-I 70% Score: 42.74. Result ID: 698fd47f3a6c314849fc2ac7.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa699f1e209131cea232a4.md>)

[Implementation](<https://github.com/pxiangwu/PLC>)

Recorded evaluation configuration: {"Noise Level":"70%"}. This record does not assert independent reproduction.

### Cross-Entropy

Type-I 70% Score: 41.98. Result ID: 698fd47f3a6c314849fc2ac6.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa671c1e209131cea144cf.md>)

[Implementation](<https://github.com/LiJunnan1992/DivideMix>)

Recorded evaluation configuration: {"Noise Level":"70%"}. This record does not assert independent reproduction.

### Bootstrapping Training Algorithm

Type-I 70% Score: 21.17. Result ID: 698fd47f3a6c314849fc2ac9.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Implementation](<https://github.com/btsmart/bootstrapping-label-noise>)

Recorded evaluation configuration: {"Model variant":"Regular Model","Noise Level":"70%","Test-Time Augmentation":true}. This record does not assert independent reproduction.

### Bootstrapping Training Algorithm

Type-I 70% Score: 21.02. Result ID: 698fd47f3a6c314849fc2ac8.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Implementation](<https://github.com/btsmart/bootstrapping-label-noise>)

Recorded evaluation configuration: {"Model variant":"Regular Model","Noise Level":"70%","Test-Time Augmentation":false}. This record does not assert independent reproduction.

### Bootstrapping Training Algorithm

Type-I 70% Score: 19.71. Result ID: 698fd47f3a6c314849fc2acb.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Implementation](<https://github.com/btsmart/bootstrapping-label-noise>)

Recorded evaluation configuration: {"Model variant":"Modified Model","Noise Level":"70%","Test-Time Augmentation":true}. This record does not assert independent reproduction.

### Bootstrapping Training Algorithm

Type-I 70% Score: 19.18. Result ID: 698fd47f3a6c314849fc2aca.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6dad1e209131cea3b71c.md>)

[Implementation](<https://github.com/btsmart/bootstrapping-label-noise>)

Recorded evaluation configuration: {"Model variant":"Modified Model","Noise Level":"70%","Test-Time Augmentation":false}. This record does not assert independent reproduction.

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