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arXiv Paper Proposes Continual Learning Method Built on Pre-trained Models
A revised arXiv preprint describes a continual learning approach that leverages pre-trained models to help systems keep earlier knowledge while picking up new tasks. The work targets catastrophic forgetting, where performance on previously learned tasks degrades as new ones are acquired. The paper is listed as a replacement submission, with no peer-reviewed venue indicated.