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.

14 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. 2026
  4. 2025PDF ↗
  5. 2025
    Dual-modality adaptation in vision-language models for continual learningJiayang Zeng, Wentao Zhang, Kanghao Chen … Ruixuan WangNeural Networks
  6. 2025
    Decoupling Continual Semantic SegmentationYifu Guo, Yu-Quan Lu, Wentao Zhang … Ruixuan WangAAAI
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  7. 2025
    STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution GeneralizationHaoyu Zhang, Wentao Zhang, H. Miao … Yifan ZhangNeurIPS
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  8. 2025
    Visual Class Incremental Learning With Textual Priors Guidance Based on an Adapted Vision-Language ModelWentao Zhang, Tong Yu, Ruixuan Wang … Xiaobo YangIEEE Trans. Multimedia
  9. 2024
    Continual Learning of Image Classes With Language Guidance From a Vision-Language ModelWentao Zhang, Yujun Huang, Wei-Zhuo Zhang … Ruixuan WangIEEE TCSVT
  10. 2024PDF ↗
  11. 2024
    QAEncoder: Towards Aligned Representation Learning in Question Answering SystemZheng-Ren Wang, Qinhan Yu, Shida Wei … Wentao ZhangACL
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  12. 2024
    Expand and Merge: Continual Learning with the Guidance of Fixed Text Embedding SpaceYujun Huang, Wentao Zhang, Ruixuan WangIEEE International Joint Conference on Neural Network
  13. 2024
    CtF: Mitigating Visual Confusion in Continual Learning Through a Coarse-To-Fine ScreeningZe-Jun Ye, Defeng Zhao, Wentao Zhang, Ruixuan WangInternational Conference on Intelligent Computing
  14. 2024
    Enhancing Task Identification Through Pseudo-OOD Features for Class-Incremental LearningWei-Zhuo Zhang, Jian-Kang Chen, Wentao Zhang … Ruixuan WangChinese Conference on Pattern Recognition and Computer Vi…
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.