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.

25 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
    An active unlearning framework for continual learningXuemei Cao, Yong-Hao Li, Xiangkun Wang … Xin YangScientia Sinica Informationis
  3. 2026
  4. 2025
    Input refinement with incremental learning for accurate digital twin-enabled self-driven QoT optimization in optical networksXin Yang, Chenyu Sun, Reda Ayassi … Y. PointurierJournal of Optical Communications and Networking
  5. 2026PDF ↗
  6. 2025PDF ↗
  7. 2025
    A Survey of Continual Reinforcement LearningChao-Fan Pan, Xin Yang, Yan-Hua Li … Jiye LiangarXiv
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  8. 2025
    ErrorEraser: Unlearning Data Bias for Improved Continual LearningXuemei Cao, Hanlin Gu, Xin Yang … Tianrui LiKDD
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  9. 2025PDF ↗
  10. 2025
    RACE: Robust adaptive and clustering elimination for noisy labels in continual learningXiaolong Yang, Guannan Lai, Dan Meng … Xin YangKnowledge-Based Systems
  11. 2025
    Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligenceXiang He, Dongcheng Zhao, Yang Li … Yi ZengScience Advances
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  12. 2025PDF ↗
  13. 2025PDF ↗
  14. 2025PDF ↗
  15. 2025
    Ten Challenging Problems in Federated Foundation ModelsTao Fan, Hanlin Gu, Xuemei Cao … Qiang YangTKDE
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  16. 2024PDF ↗
  17. 2024
    Unleashing the Power of Continual Learning on Non-Centralized Devices: A SurveyYi-Chen Li, Haozhao Wang, Wenchao Xu … Ruixuan LiIEEE Communications Surveys and Tutorials
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  18. 2024
  19. 2024PDF ↗
  20. 2024PDF ↗
  21. 2024
    Open Continual Feature Selection via Granular-Ball Knowledge TransferXuemei Cao, Xin Yang, Shuyin Xia … Tianrui LiTKDE
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  22. 2024
  23. 2023
    Federated Continual Learning via Knowledge Fusion: A SurveyXin Yang, Hao Yu, Xin Gao … Tianrui LiTKDE
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  24. 2023PDF ↗
  25. 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.