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Class-Incremental Learning on ImageNet-A 10% samples (test)

Class-Incremental Learning on ImageNet-A 10% samples (test)

52.9AccuracySEMA

Updated 8mo ago

Evaluation results

Method	Links
SEMA2024.03		52.9	41.41
EASE2024.03		52.79	41.67

State-of-the-art paper

SEMA

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

Dataset

ImageNet-A

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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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