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.

10 papers of 8,653Sort Recent · Most cited
  1. 2025
    A theory of initialisation’s impact on specialisationDevon Jarvis, Sebastian Lee, Clémentine Carla Juliette Dominé … Stefano Sarao MannelliICLR · University of the Witwatersrand · Simons Foundation · +6
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  2. 2024
    Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer LearningL. Frati, Neil Traft, Jeff Clune, Nick CheneyFrontiers · University of Vermont · Canadian Institute for Advanced Research · +2
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  3. 2024
    Loss of plasticity in deep continual learningShibhansh Dohare, Juan Hernandez-Garcia, Qingfeng Lan … Richard S. SuttonNature · University of Alberta · Canadian Institute for Advanced Research
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  4. 2022
    Exact learning dynamics of deep linear networks with prior knowledgeClémentine Dominé, Lukas Braun, James E. Fitzgerald, Andrew SaxeNeurIPS · Gatsby Computational Neuroscience Unit · University College London · +4
  5. 2023
    Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signalsTimo Flesch, Dávid Nagy, Andrew Saxe, Christopher SummerfieldPLOS · University of Oxford · HUN-REN Wigner Research Centre for Physics · +5
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  6. 2021
    Understanding Capacity Saturation in Incremental LearningShenyang Huang, Vincent François-Lavet, Guillaume RabusseauCanadian Conference on Artificial Intelligence · Centre Universitaire de Mila · McGill University · +3
  7. 2021
    IIRC: Incremental Implicitly-Refined ClassificationMohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani, Sarath ChandarCVPR · Mila - Quebec Artificial Intelligence Institute · Université de Montréal · +3
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  8. 2021
    AdapterFusion: Non-Destructive Task Composition for Transfer LearningJonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé … Iryna GurevychEACL · Technische Universität Darmstadt · Supélec · +5
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  9. 2021
    Continual Learning with Dual RegularizationsXuejun Han, Yuhong GuoSpringer LNCS · Carleton University · Canadian Institute for Advanced Research
  10. 2019
    Gradient based sample selection for online continual learningRahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua BengioNeurIPS · KU Leuven · National University of Singapore · +1
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.