Continual Learning
Learning new tasks without forgetting old ones.
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.
Top 10
Leading models on Split CIFAR-100.
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All datasets
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Related tasks
Other tasks in Methodology.
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