Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

3 papers of 8,653Sort Recent · Most cited
  1. 2024
    Saliency-driven Experience Replay for Continual LearningGiovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi … Concetto SpampinatoNeurIPS
  2. 2022
    On the Effectiveness of Lipschitz-Driven Rehearsal in Continual LearningLorenzo Bonicelli, M. Boschini, Angelo Porrello … Simone CalderaraNeurIPS
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  3. 2020
    Dark Experience for General Continual Learning: a Strong, Simple BaselinePietro Buzzega, Matteo Boschini, Angelo Porrello … Simone CalderaraNeurIPS · University of Modena and Reggio Emilia
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.