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In the context of continual learning, prototypes-as representative class embeddings-offer advantages in memory conservation and the mitigation of catastrophic forgetting.
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Visual prompt tuning
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Fine-tuning can distort pretrained features and underperform out-of-distribution
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Forward compatible few-shot class-incremental learning, 2022
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Isolation and impartial aggregation: A paradigm of incremental learning without interference
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