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.

7 papers of 11,817Sort Recent · Most cited
  1. 2026
    TASSO: TAsk-Specific Subspace Optimization for Continual Learning of Vision-Language ModelsChangming Sun, Francesco Barbato, Matteo Caligiuri, Pietro ZanuttigharXiv
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  2. 2024PDF ↗
  3. 2022
    Learning With Style: Continual Semantic Segmentation Across Tasks and DomainsMarco Toldo, Umberto Michieli, Pietro ZanuttighTPAMI · University of Padua
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  4. 2021
    RECALL: Replay-based Continual Learning in Semantic SegmentationAndrea Maracani, Umberto Michieli, Marco Toldo, Pietro ZanuttighICCV · University of Padua
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  5. 2021PDF ↗
  6. 2019
    Knowledge Distillation for Incremental Learning in Semantic SegmentationUmberto Michieli, Pietro ZanuttighComputer Vision and Image Understanding · University of Padua
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  7. 2019
    Incremental Learning Techniques for Semantic SegmentationUmberto Michieli, Pietro ZanuttighICCV · University of Padua
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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.