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.

4 papers of 11,817Sort Recent · Most cited
  1. 2024
    The Expanding Scope of the Stability Gap: Unveiling its Presence in Joint Incremental Learning of Homogeneous TasksSandesh Kamath, Albin Soutif-Cormerais, J. van de Weijer, Bogdan RaducanuCVPR
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  2. 2024
    Resurrecting Old Classes with New Data for Exemplar-Free Continual LearningDipam Goswami, Albin Soutif-Cormerais, Yuyang Liu … J. WeijerCVPR
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  3. 2024
    An Empirical Analysis of Forgetting in Pre-trained Models with Incremental Low-Rank UpdatesAlbin Soutif-Cormerais, Simone Magistri, J. Weijer, Andew D. BagdanovCoLLAs
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  4. 2024
    Elastic Feature Consolidation for Cold Start Exemplar-free Incremental LearningSimone Magistri, Tomaso Trinci, Albin Soutif-Cormerais … Andrew D. BagdanovICLR
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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.