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
    Overcoming classic challenges for artificial neural networks by providing incentives and practiceKazuki Irie, Brenden M. LakeNature Machine Intelligence · Harvard University · Princeton University
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  2. 2025
    Preserving and combining knowledge in robotic lifelong reinforcement learningYuan Meng, Zhenshan Bing, Xiangtong Yao … Alois KnollNature Machine Intelligence · Technical University of Munich · Nanjing University · +2
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  3. 2024
    Engineering flexible machine learning systems by traversing functionally invariant pathsGuruprasad Raghavan, Bahey Tharwat, Surya N. Hari … Matt ThomsonNature Machine Intelligence · California Institute of Technology · Superior Court of California · +1
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  4. 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
  5. 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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  6. 2023
  7. 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
  8. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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  9. 2020
    Rapid online learning and robust recall in a neuromorphic olfactory circuitNabil Imam, Thomas A. ClelandNature Machine Intelligence · Intel (United States) · Cornell University
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  10. 2019
    Continual learning of context-dependent processing in neural networksGuanxiong Zeng, Yang Chen, Bo Cui, Shan YuNature Machine Intelligence · Chinese Academy of Sciences · Institute of Automation · +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. 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.