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Continual Learning on VTAB-1

Continual Learning on VTAB-1

86.74Avg Accuracy (A-bar)SEMA

Updated 8mo ago

Evaluation results

Method	Links
SEMA2024.03		86.74	81.33
EASE2024.03		86.56	78.37

State-of-the-art paper

SEMA

Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning

Dataset

VTAB

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Related benchmarks

Continual Learning on CIFAR-100 (Training Time)Continual Learning on ImageNet A Training Time on VTAB (Continual Learning)Class-Incremental Learning on ImageNet-R 50 tasks (test)Class-Incremental Learning on ImageNet-A 50 tasks (test)

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