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Re-evaluating Continual Learning with Few-Shot Adaptation

Few-shot evaluation of continual learning reveals that meta-learning future tasks improves per-shot plasticity and stability across sequences.

Amogh Inamdar, Matthew So, Vici I Milenia, Richard Zemel

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
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strict 1/5