# Image Classification on CIFAR-100N 1.0 (test) Source: [Image Classification on CIFAR-100N 1.0 (test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:34:21.745Z Evaluation of Image Classification performance on the test split of the CIFAR-100N dataset, version 1.0, specifically reporting noisy accuracy. 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-100N 1.0 (test) | | Metric | Accuracy (Noisy) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 12 of 12 | | 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 (Noisy)](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy (Noisy) | Result date | Report paper | | --- | --- | --- | --- | | GNL - p(X,Y) | 62.34 | Not recorded | 68fa72531e209131cea55a73 | | CAL | 61.73 | Not recorded | 68fa72531e209131cea55a73 | | CORES^2 | 61.15 | Not recorded | 68fa72531e209131cea55a73 | | GNL - p(Y\|X) | 59.03 | Not recorded | 68fa72531e209131cea55a73 | | Negative-LS | 58.59 | Not recorded | 68fa72531e209131cea55a73 | | VolMinNet | 57.8 | Not recorded | 68fa72531e209131cea55a73 | | Peer Loss | 57.59 | Not recorded | 68fa72531e209131cea55a73 | | F-Div | 57.1 | Not recorded | 68fa72531e209131cea55a73 | | Forward T | 57.01 | Not recorded | 68fa72531e209131cea55a73 | | Positive-LS | 55.84 | Not recorded | 68fa72531e209131cea55a73 | | CE | 55.5 | Not recorded | 68fa72531e209131cea55a73 | | T-Revision | 51.55 | Not recorded | 68fa72531e209131cea55a73 | ### GNL - p(X,Y) Accuracy (Noisy): 62.34. Result ID: 699230913a6c3148490d2e5f. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### CAL Accuracy (Noisy): 61.73. Result ID: 699230913a6c3148490d2e5d. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### CORES^2 Accuracy (Noisy): 61.15. Result ID: 699230913a6c3148490d2e5b. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### GNL - p(Y\|X) Accuracy (Noisy): 59.03. Result ID: 699230913a6c3148490d2e5e. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### Negative-LS Accuracy (Noisy): 58.59. Result ID: 699230913a6c3148490d2e5a. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### VolMinNet Accuracy (Noisy): 57.8. Result ID: 699230913a6c3148490d2e5c. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### Peer Loss Accuracy (Noisy): 57.59. Result ID: 699230913a6c3148490d2e57. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### F-Div Accuracy (Noisy): 57.1. Result ID: 699230913a6c3148490d2e59. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### Forward T Accuracy (Noisy): 57.01. Result ID: 699230913a6c3148490d2e55. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### Positive-LS Accuracy (Noisy): 55.84. Result ID: 699230913a6c3148490d2e58. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### CE Accuracy (Noisy): 55.5. Result ID: 699230913a6c3148490d2e54. [Reporting paper]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. ### T-Revision Accuracy (Noisy): 51.55. Result ID: 699230913a6c3148490d2e56. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"ResNet-34","Classifier Type":"single classifier"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.