# Image Classification on CIFAR-10 (test) (Adversarial Accuracy) Source: [Image Classification on CIFAR-10 (test) (Adversarial Accuracy)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:39:18.798Z Evaluation of Image Classification performance on the CIFAR-10 test set, specifically reporting Clean Accuracy, Adversarial Accuracy, and their Average, typically used for robustness assessment. 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 | 8 of 8 | | 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](): Higher is better; unit: PERCENT. - [Adversarial Accuracy](): Higher is better; unit: PERCENT. - [Average Accuracy](): Higher is better; unit: PERCENT. ## Recorded results | Method | Clean Accuracy | Result date | Report paper | | --- | --- | --- | --- | | Vanilla | 74.75 | Not recorded | 69438a6f423ea42265729342 | | Vanilla | 74.36 | Not recorded | 69438a6f423ea42265729342 | | FedDistFed | 72.43 | Not recorded | 69438a6f423ea42265729342 | | FedDistFed | 71.42 | Not recorded | 69438a6f423ea42265729342 | | FedDist | 70.49 | Not recorded | 69438a6f423ea42265729342 | | FAT | 70.47 | Not recorded | 69438a6f423ea42265729342 | | FAT | 68.85 | Not recorded | 69438a6f423ea42265729342 | | FedDist | 66.23 | Not recorded | 69438a6f423ea42265729342 | ### Vanilla Clean Accuracy: 74.75. Result ID: 699959555698665ec4c4da08. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ConvNet","Tc (ms)":"10.07"}. This record does not assert independent reproduction. ### Vanilla Clean Accuracy: 74.36. Result ID: 699959555698665ec4c4da0c. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"AlexNet","Tc (ms)":"9.76"}. This record does not assert independent reproduction. ### FedDistFed Clean Accuracy: 72.43. Result ID: 699959555698665ec4c4da0b. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ConvNet","Tc (ms)":"20.14"}. This record does not assert independent reproduction. ### FedDistFed Clean Accuracy: 71.42. Result ID: 699959555698665ec4c4da0f. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"AlexNet","Tc (ms)":"19.52"}. This record does not assert independent reproduction. ### FedDist Clean Accuracy: 70.49. Result ID: 699959555698665ec4c4da0a. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ConvNet","Tc (ms)":"10.07"}. This record does not assert independent reproduction. ### FAT Clean Accuracy: 70.47. Result ID: 699959555698665ec4c4da09. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ConvNet","Tc (ms)":"16.45"}. This record does not assert independent reproduction. ### FAT Clean Accuracy: 68.85. Result ID: 699959555698665ec4c4da0d. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"AlexNet","Tc (ms)":"15.12"}. This record does not assert independent reproduction. ### FedDist Clean Accuracy: 66.23. Result ID: 699959555698665ec4c4da0e. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"AlexNet","Tc (ms)":"9.76"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.