Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

14 papers of 6,984Sort Recent · Most cited
  1. 2025
    Continual Learning in the Presence of RepetitionHamed Hemati, Lorenzo Pellegrini, X.W. Duan … Gido M. van de VenNeural Networks · University of St.Gallen · University of Applied Sciences St. Gallen · +10
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  2. 2024
    Efficient distributed continual learning for steering experiments in real-timeThomas Bouvier, Bogdan Nicolae, Alexandru Costan … Gabriel AntoniuFuture Generation Computer Systems · Centre National de la Recherche Scientifique · Institut de Recherche en Informatique et Systèmes Aléatoires · +4
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  3. 2024
    Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal BuffersThomas Bouvier, Bogdan Nicolae, Hugo Chaugier … Gabriel AntoniuIEEE/ACM International Symposium on Cluster, Cloud and In… · Centre National de la Recherche Scientifique · Institut de Recherche en Informatique et Systèmes Aléatoires · +3
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  4. 2023
    Design principles for lifelong learning AI acceleratorsDhireesha Kudithipudi, Anurag Daram, Abdullah M. Zyarah … Benjamin R. EpsteinNature Electronics · The University of Texas at San Antonio · Sandia National Laboratories · +6
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  5. 2023
    A Domain-Agnostic Approach for Characterization of Lifelong Learning SystemsMegan M. Baker, Alexander New, Mario Aguilar-Simon … Gautam K. VallabhaNeural Networks · Johns Hopkins University Applied Physics Laboratory · Teledyne Technologies (United States) · +13
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  6. 2022
    Continual Learning via Dynamic ProgrammingRanganath Krishnan, Prasanna BalaprakashICPR · Argonne National Laboratory
  7. 2022
    Large Scale Caching and Streaming of Training Data for Online Deep LearningJie Liu, Bogdan Nicolae, Dong Li … Ian FosterWorkshop on AI and Scientific Computing at Scale using Fl… · University of California, Merced · Argonne National Laboratory
  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. 2021
    Formalizing the Generalization-Forgetting Trade-off in Continual LearningKrishnan Raghavan, Prasanna BalaprakashNeurIPS · Argonne National Laboratory
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  10. 2020
    Exploring Neuromodulation for Dynamic LearningAnurag Daram, Ángel Yanguas-Gil, Dhireesha KudithipudiFrontiers · The University of Texas at San Antonio · Argonne National Laboratory
  11. 2020
    Meta Continual Learning via Dynamic ProgrammingKrishnan, R., Prasanna BalaprakasharXiv · Argonne National Laboratory
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  12. 2020
    Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual LearningSandeep Madireddy, Ángel Yanguas-Gil, Prasanna BalaprakasharXiv · Argonne National Laboratory
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  13. 2019
    Task-Based Neuromodulation Architecture for Lifelong LearningAnurag Daram, Dhireesha Kudithipudi, Ángel Yanguas-GilInternational Symposium on Quality Electronic Design (ISQED) · Rochester Institute of Technology · Argonne National Laboratory
  14. 2017
    Habituation based synaptic plasticity and organismic learning in a quantum perovskiteFan Zuo, Priyadarshini Panda, Michele Kotiuga … Shriram RamanathanNature Communications · Purdue University West Lafayette · Rutgers, The State University of New Jersey · +3
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 led 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.