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. 2024
    A collective AI via lifelong learning and sharing at the edgeAndrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman … Soheil KolouriNature Machine Intelligence · Loughborough University · Rice University · +21
  2. 2022
    CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual LearningJames Seale Smith, Leonid Karlinsky, Vyshnavi Gutta … Zsolt KiraCVPR · Georgia Institute of Technology · IBM (United States) · +1
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  3. 2022
    Three types of incremental learningGido M. van de Ven, Tinne Tuytelaars, Andreas S. ToliasNature Machine Intelligence · Baylor College of Medicine · University of Cambridge · +2
  4. 2020
    Brain-inspired replay for continual learning with artificial neural networksGido M. van de Ven, Hava T. Siegelmann, Andreas S. ToliasNature Communications · Baylor College of Medicine · University of Cambridge · +3
  5. 2018
    HOUDINI: Lifelong Learning as Program SynthesisLazar Valkov, Dipak Chaudhari, Akash Srivastava … Swarat ChaudhuriNeurIPS · Indian Institute of Technology Bombay · IBM (United States) · +2
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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.