Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 8,653Sort Recent · Most cited
  1. 2025
    Collaborative Adapter Experts for Class-Incremental LearningSunyuan Qiang, Xinxing Yu, Yanyan Liang … Du ZhangIEEE Signal Processing Letters · Macau University of Science and Technology · Chinese Academy of Sciences · +1
  2. 2024
    Adapt and Refine: A Few-Shot Class-Incremental Learner via Pre-Trained ModelsSunyuan Qiang, Xiong Zhu, Yanyan Liang … Du ZhangSpringer LNCS · Macau University of Science and Technology · Chinese Academy of Sciences · +2
  3. 2024
    FeTT: Continual Class Incremental Learning via Feature Transformation TuningSunyuan Qiang, Xuxin Lin, Yanyan Liang … Du ZhangarXiv
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  4. 2024
    Dynamic Feature Learning and Matching for Class-Incremental LearningSunyuan Qiang, Yanyan Liang, Jun Wan, Du ZhangarXiv
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  5. 2024
    Continual Learning on Graphs: A SurveyZonggui Tian, Du Zhang, Hong‐Ning DaiarXiv
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  6. 2023
    Mixture Uniform Distribution Modeling and Asymmetric Mix Distillation for Class Incremental LearningSunyuan Qiang, Jiayi Hou, Jun Wan … Du ZhangAAAI · Macau University of Science and Technology · Lafayette College · +2
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  7. 2020
    A Perpetual Learning Algorithm That Incrementally Improves Performance With DeliberationHaiou Qin, Du ZhangIEEE Access · Macau University of Science and Technology
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.