Continual Learning

Learning new tasks without forgetting old ones.

1
Datasets
3
Results
average_accuracy
Canonical metric
Canonical Benchmark

Split CIFAR-100

Canonical class-incremental continual learning benchmark: CIFAR-100 is split into 10 sequential tasks of 10 classes each. Models learn tasks one at a time without access to prior-task data and are evaluated on average accuracy across all tasks after the full sequence.

Primary metric: average_accuracy
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Top 10

Leading models on Split CIFAR-100.

RankModelaverage_accuracyYearSource
1
SLCA (ViT-B/16)
91.52026paper
2
DualPrompt (ViT-B/16)
86.52026paper
3
L2P (ViT-B/16)
83.92026paper

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