Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 5,456Sort 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. 2026
    Schedule-Robust Continual LearningRuohan Wang, Marco Ciccone, Massimiliano Pontil, Carlo CilibertoTPAMI · Agency for Science, Technology and Research · Institute for Infocomm Research · +3
  3. 2023
    Incorporating neuro-inspired adaptability for continual learning in artificial intelligenceLiyuan Wang, Xingxing Zhang, Qian Li … Yi ZhongNature Machine Intelligence · Chinese Institute for Brain Research · Center for Life Sciences · +2
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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
    Continual task learning in natural and artificial agentsTimo Flesch, Andrew Saxe, Christopher SummerfieldTrends in Neurosciences · University of Oxford · Sainsbury Laboratory · +3
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  6. 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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  7. 2023
    Efficient Continual Learning in Reservoir NetworksPaul Okeahalam, Liang Zhou, Jorge Aurelio Menendez, Peter E. LathamConference on Cognitive Computational Neuroscience · University College London
  8. 2022
    An analytical theory of curriculum learning in teacher–student networksLuca Saglietti, Stefano Sarao Mannelli, Andrew SaxeNeurIPS · Bocconi University · Gatsby Computational Neuroscience Unit · +1
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  9. 2021
    AFEC: Active Forgetting of Negative Transfer in Continual LearningLiyuan Wang, Ming‐Tian Zhang, Zhongfan Jia … Yi ZhongNeurIPS · Tsinghua University · University College London
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  10. 2021
    IncDet: In Defense of Elastic Weight Consolidation for Incremental Object DetectionLiyang Liu, Zhanghui Kuang, Yimin Chen … Wayne ZhangTNNLS · University Town of Shenzhen · Tsinghua University · +2
  11. 2021
    Addressing Catastrophic Forgetting in Few-Shot ProblemsPauching Yap, Hippolyt Ritter, David BarberICML · University College London
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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 lists only 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. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.