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.

34 papers of 11,817Sort Recent · Most cited
  1. 2026
    Continual Learning across multiple domains via a Dynamic Expandable and Mergeable ModelFei Ye, Ruilong Yu, Qihe Liu … Kun ZhangEng. Applications of AI
  2. 2026
    Continual learning via dynamic expandable task-specific and general representationsQihe Liu, Yong Zhong, Fei Ye … Shi-Jie ZhouKnowledge-Based Systems
  3. 2026
    Continual learning via semantic memory systemMing-Sen Luo, Qi-He Liu, Fei Ye … Shi-Jie ZhouPattern Recognition
  4. 2026
    Learning Adaptive and Expandable Mixture Model for Continual LearningFei Ye, Yong Zhong, Qihe Liu … Shi-Jie ZhouAAAI
  5. 2026PDF ↗
  6. 2026
    Continual Learning Via Gradient-Regularized Based Dynamic Expansion ModelFei Ye, Yong Zhong, Qi-He Liu … Shi-Jie ZhouIEEE Trans. Multimedia
  7. 2025
  8. 2025PDF ↗
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  19. 2025
    Learning Expandable and Adaptable Representations for Continual LearningRuilong Yu, Mingyang Liu, Fei Ye … Shijie ZhouNeurIPS
  20. 2025
    Learning Multi-Source and Robust Representations for Continual LearningFei Ye, Yong Zhong, Qihe Liu … Shi-Jie ZhouNeurIPS
  21. 2024
  22. 2024
    Temporal Transformer Encoder for Video Class Incremental LearningNattapong Kurpukdee, A. BorsInternational Conference on Information Photonics
  23. 2024
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  26. 2023
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  34. 2023
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.