Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

9 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
    Rising From Pieces: Effective Inference at the Edge via Robust Split MLYuxuan Weng, Tianyue Zheng, Zhe Chen … Jun LuoIEEE Transactions
  3. 2025PDF ↗
  4. 2025
    Reinitializing weights vs units for maintaining plasticity in neural networksJ. Hernandez-Garcia, Shibhansh Dohare, Jun Luo, Richard S. SuttonarXiv
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  5. 2025PDF ↗
  6. 2025
    Enabling Passive User Authentication via Heart Sounds on In-Ear MicrophonesYetong Cao, Chao Cai, Fan Li … Jun LuoIEEE Transactions
  7. 2023
    HeartPrint: Passive Heart Sounds Authentication Exploiting In-Ear MicrophonesYetong Cao, Chao Cai, Fan Li … Jun LuoIEEE Conference on Computer Communications
  8. 2022
    Memory-efficient Reinforcement Learning with Value-based Knowledge ConsolidationQingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam MahmoodTrans. Mach. Learn. Res.
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  9. 2020PDF ↗
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 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.