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.

6 papers of 11,817Sort Recent · Most cited
  1. 2024
    Mask and Compress: Efficient Skeleton-based Action Recognition in Continual LearningMatteo Mosconi, Andriy Sorokin, Aniello Panariello … R. CucchiaraICPR
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  2. 2024
    Federated Class-Incremental Learning with Hierarchical Generative PrototypesRiccardo Salami, Pietro Buzzega, Matteo Mosconi … S. CalderaraTrans. Mach. Learn. Res.
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  3. 2023
    On the Effectiveness of Equivariant Regularization for Robust Online Continual LearningLorenzo Bonicelli, Matteo Boschini, Emanuele Frascaroli … S. CalderaraarXiv
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  4. 2023
    Neuro Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept RehearsalE. Marconato, G. Bontempo, E. Ficarra … Stefano TesoICML
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  5. 2023
    CaSpeR: Latent Spectral Regularization for Continual LearningEmanuele Frascaroli, Riccardo Benaglia, Matteo Boschini … S. CalderaraPattern Recognition Letters
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  6. 2021
    Weakly Supervised Continual LearningMatteo Boschini, Pietro Buzzega, Lorenzo Bonicelli … S. CalderaraarXiv
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.