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.

7 papers of 11,817Sort Recent · Most cited
  1. 2025
    Continual Knowledge Adaptation for Reinforcement LearningJinwu Hu, Zihao Lian, Z. Wen … Mingkui TanNeurIPS
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  2. 2025
    Test-Time Learning for Large Language ModelsJinwu Hu, Zhitian Zhang, Guohao Chen … Mingkui TanICML
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  3. 2025
    Source-Free Elastic Model Adaptation for Vision-and-Language NavigationMingkui Tan, Peihao Chen, Hongyan Zhi … Runhao ZengIEEE Trans. Multimedia
  4. 2024
    Uncertainty-Calibrated Test-Time Model Adaptation Without ForgettingMingkui Tan, Guohao Chen, Jiaxiang Wu … Shuaicheng NiuTPAMI
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  5. 2022PDF ↗
  6. 2022
    Efficient Test-Time Model Adaptation without ForgettingShuaicheng Niu, Jiaxiang Wu, Yifan Zhang … Mingkui TanICML
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  7. 2019
    Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-CorrectionFengda Zhu, Xiaojun Chang, Runhao Zeng, Mingkui TanarXiv · South China University of Technology
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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.