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.

5 papers of 8,653Sort Recent · Most cited
  1. 2025
    EFC++: Elastic Feature Consolidation with Prototype Re-balancing for Cold Start Exemplar-free Incremental LearningSimone Magistri, Tomaso Trinci, Albin Soutif-Cormerais … Andrew D. BagdanovarXiv
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  2. 2024
    Incremental and Decremental Continual Learning for Privacy-Preserving Video RecognitionLorenzo Caselli, Simone Magistri, Tommaso Bianconcini … Andrew D. BagdanovSpringer LNCS · University of Florence · Serviço Nacional de Aprendizagem Industrial
  3. 2024PDF ↗
  4. 2024
    An Empirical Analysis of Forgetting in Pre-trained Models with Incremental Low-Rank UpdatesAlbin Soutif--Cormerais, Simone Magistri, Joost van de Weijer, Andew D. BagdanovCoLLAs
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  5. 2024
    Elastic Feature Consolidation for Cold Start Exemplar-free Incremental LearningSimone Magistri, Tomaso Trinci, Albin Soutif--Cormerais … Andrew D. BagdanovICLR
    PDF ↗
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.