# Class-incremental Classification on ImageNet-100 50 tasks Source: [Class-incremental Classification on ImageNet-100 50 tasks]() Collection index: [llms.txt]() Data updated: 2026-07-01T07:34:12.721Z Evaluation of model performance using Class-incremental Classification methodology on the ImageNet-100 dataset configured for 50 incremental tasks. 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 | Class-incremental Classification | | Dataset (including any stated split) | ImageNet-100 50 tasks | | Metric | Cumulative Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 7 of 7 | | 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 - [Cumulative Accuracy](): Higher is better; unit: PERCENT. - [Forward Accuracy](): Higher is better; unit: PERCENT. ## Recorded results | Method | Cumulative Accuracy | Result date | Report paper | | --- | --- | --- | --- | | CLIMB | 46.22 | Not recorded | 6a449eefe0224bd4f4992dd4 | | CLA-E | 43.39 | Not recorded | 6a449eefe0224bd4f4992dd4 | | PCMC | 42.65 | Not recorded | 6a449eefe0224bd4f4992dd4 | | CLA-R | 40.41 | Not recorded | 6a449eefe0224bd4f4992dd4 | | Osiris-R | 35.64 | Not recorded | 6a449eefe0224bd4f4992dd4 | | MinRed | 34.83 | Not recorded | 6a449eefe0224bd4f4992dd4 | | SCALE | 29.26 | Not recorded | 6a449eefe0224bd4f4992dd4 | ### CLIMB Cumulative Accuracy: 46.22. Result ID: 6a44c2f373d097d845be81ef. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### CLA-E Cumulative Accuracy: 43.39. Result ID: 6a44c2f373d097d845be81ee. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### PCMC Cumulative Accuracy: 42.65. Result ID: 6a44c2f373d097d845be81f0. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"pretraining":"false"}. This record does not assert independent reproduction. ### CLA-R Cumulative Accuracy: 40.41. Result ID: 6a44c2f373d097d845be81ed. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### Osiris-R Cumulative Accuracy: 35.64. Result ID: 6a44c2f373d097d845be81eb. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### MinRed Cumulative Accuracy: 34.83. Result ID: 6a44c2f373d097d845be81ec. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### SCALE Cumulative Accuracy: 29.26. Result ID: 6a44c2f373d097d845be81ea. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.