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.

10 papers of 6,984Sort Recent · Most cited
  1. 2025
    A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual LearningJun, James P, Vijay Marupudi, Raj Sanjay Shah, Sashank VarmaCognitive Science
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  2. 2024
    Latent Relations at Steady-state with Associative NetsKevin D. Shabahang, Hyungwook Yim, Simon DennisCognitive Science
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  3. 2024
    CORE: Mitigating Catastrophic Forgetting in Continual Learning through Cognitive ReplayJianshu Zhang, Yankai Fu, Ziheng Peng … Kun HeCognitive Science
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  4. 2024
  5. 2024
    Random Replaying Consolidated Knowledge in the Continual Learning ModelGuanglu Wang, Xinyue Liu, Wenxin Liang … Xianchao ZhangCognitive Science
  6. 2022
    A Neural Network Model of Continual Learning with Cognitive ControlJacob Russin, Maryam Zolfaghar, Seongmin A. Park … Randall C. O’ReillyCognitive Science
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  7. 2020
    Sequential Presentation Protects Working Memory From Catastrophic InterferenceAnsgar D. Endress, Szilárd SzabóCognitive Science · City, University of London · Budapest University of Technology and Economics
  8. 2019
  9. 2018
    Catastrophic Interference in Neural Embedding ModelsPrudhvi Raj Dachapally, Michael N. JonesCognitive Science
  10. 1991
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.