arXiv Machine Learning June 2, 2026 By Anushka Tiwari, Kaiyi Ji

Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning

Read the original on arXiv Machine Learning →

arXiv:2606. 01379v1 Announce Type: new Abstract: While prompt-based parameter-efficient continual learning mitigates catastrophic forgetting by isolating task-specific prompts, this isolation also limits later tasks from improving earlier ones, leaving backward knowledge transfer underexplored.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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Rethinking Transfer in Continual Learning: A Replay-Based Realisation

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When Does Continual Learning Require Learning

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