Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 11,817Sort Recent · Most cited
  1. 2026
    Dream2Learn: Structured Generative Dreaming for Continual LearningSalvatore Calcagno, M. Pennisi, Federica Proietto Salanitri … Giovanni BellittoInternational Journal of Computer Vision
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  2. 2024
    FedRewind: Rewinding Continual Model Exchange for Decentralized Federated LearningLuca Palazzo, M. Pennisi, F. Salanitri … C. SpampinatoICPR
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  3. 2024
    Selective Attention-based Modulation for Continual LearningGiovanni Bellitto, F. Salanitri, M. Pennisi … C. SpampinatoarXiv
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  4. 2024
    Saliency-driven Experience Replay for Continual LearningGiovanni Bellitto, F. Salanitri, M. Pennisi … C. SpampinatoNeurIPS
  5. 2023
    Wake-Sleep Consolidated LearningAmelia Sorrenti, Giovanni Bellitto, F. Salanitri … C. SpampinatoTNNLS
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  6. 2023
    Selective Freezing for Efficient Continual LearningAmelia Sorrenti, Giovanni Bellitto, F. Salanitri … S. PalazzoICCV
  7. 2023
    Experience Replay as an Effective Strategy for Optimizing Decentralized Federated LearningM. Pennisi, F. Salanitri, Giovanni Bellitto … Marco AldinucciICCV
  8. 2023
    On the Effectiveness of Equivariant Regularization for Robust Online Continual LearningLorenzo Bonicelli, Matteo Boschini, Emanuele Frascaroli … S. CalderaraarXiv
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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.