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
    Pattern in Motion: Retrieval-Augmented Learning for Dynamic Spatio-Temporal Graphs.Haoyu Zhang, Xinke Jiang, Wentao Zhang … Heqing HuangTPAMI
  2. 2026PDF ↗
  3. 2025
    TRAIL: Joint Inference and Refinement of Knowledge Graphs with Large Language ModelsXinkui Zhao, Hao-De Li, Yifan Zhang … Yue-Shen XuarXiv
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  4. 2025
    STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution GeneralizationHaoyu Zhang, Wentao Zhang, H. Miao … Yifan ZhangNeurIPS
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  5. 2024
    Uncertainty-Calibrated Test-Time Model Adaptation Without ForgettingMingkui Tan, Guohao Chen, Jiaxiang Wu … Shuaicheng NiuTPAMI
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  6. 2023PDF ↗
  7. 2022PDF ↗
  8. 2022
    Efficient Test-Time Model Adaptation without ForgettingShuaicheng Niu, Jiaxiang Wu, Yifan Zhang … Mingkui TanICML
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  9. 2021
    How Well Does Self-Supervised Pre-Training Perform with Streaming Data?Dapeng Hu, Shipeng Yan, Qizhengqiu Lu … Jiashi FengICLR
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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.