# Training Data Provenance Verification on CIFAR100

Source: [Training Data Provenance Verification on CIFAR100](<https://www.sota2.com/research/sota/training-data-provenance-verification-on-cifar100>)

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

Data updated: 2026-02-26T05:30:23.415Z

Evaluation of model performance on verifying the origin or provenance of training data used for models trained on the CIFAR-100 dataset, measured using accuracy, F1 score, and AUC.

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 | Training Data Provenance Verification |
| Dataset (including any stated split) | CIFAR100 |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 5 of 5 |
| 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

- [Accuracy](<https://www.sota2.com/research/sota/training-data-provenance-verification-on-cifar100.md?metric=Accuracy>): Higher is better; unit: PERCENT.

- [F1 Score](<https://www.sota2.com/research/sota/training-data-provenance-verification-on-cifar100.md?metric=F1%20Score>): Higher is better; unit: PERCENT.

- [AUC](<https://www.sota2.com/research/sota/training-data-provenance-verification-on-cifar100.md?metric=AUC>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| TrainProVe | 99.2 | Not recorded | 68fa77671e209131cea730fb |
| Han et al.'s Work | 73 | Not recorded | 68fa77671e209131cea730fb |
| TrainProVe-Sim | 57.5 | Not recorded | 68fa77671e209131cea730fb |
| Random | 50 | Not recorded | 68fa77671e209131cea730fb |
| TrainProVe-Ent | 39.8 | Not recorded | 68fa77671e209131cea730fb |

### TrainProVe

Accuracy: 99.2. Result ID: 69949d523a6c3148491e69a9.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Implementation](<https://github.com/xieyc99/TrainProVe>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### Han et al.'s Work

Accuracy: 73. Result ID: 69949d523a6c3148491e69a6.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### TrainProVe-Sim

Accuracy: 57.5. Result ID: 69949d523a6c3148491e69a7.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Implementation](<https://github.com/xieyc99/TrainProVe>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### Random

Accuracy: 50. Result ID: 69949d523a6c3148491e69a5.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### TrainProVe-Ent

Accuracy: 39.8. Result ID: 69949d523a6c3148491e69a8.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77671e209131cea730fb.md>)

[Implementation](<https://github.com/xieyc99/TrainProVe>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

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