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.

17 papers of 11,817Sort Recent · Most cited
  1. 2026
    Continual Low-Rank Adaptation Via Cumulative Unified Optimization.Yue Lu, Shizhou Zhang, De Cheng … Yanning ZhangTPAMI
  2. 2025
    YOLO-IOD: Towards Real Time Incremental Object DetectionShizhou Zhang, Xueqiang Lv, Yinghui Xing … Yanning ZhangAAAI
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  3. 2025
  4. 2025
  5. 2025
    Gradient Decomposition and Alignment for Incremental Object DetectionWenlong Luo, Shizhou Zhang, De Cheng … Yanning ZhangICCV
  6. 2025
  7. 2025PDF ↗
  8. 2025
    Revisiting Generative Replay for Class Incremental Object DetectionShizhou Zhang, Xueqiang Lv, Yinghui Xing … Yanning ZhangCVPR
  9. 2025
  10. 2025
    Demystifying Catastrophic Forgetting in Two-Stage Incremental Object DetectorQirui Wu, Shizhou Zhang, De Cheng … Yanning ZhangICML
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  11. 2024
    A masking, linkage and guidance framework for online class incremental learningGuoqiang Liang, Zhao-Jie Chen, Shibin Su … Yanning ZhangPattern Recognition
  12. 2024
    Sustainable Self-evolution Adversarial TrainingWenxuan Wang, Chenglei Wang, Huihui Qi … Yanning ZhangACM MM
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  13. 2024
    Visual Prompt Tuning in Null Space for Continual LearningYue Lu, Shizhou Zhang, De Cheng … Yanning ZhangNeurIPS
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  14. 2024
  15. 2023
    Optimal Policy Replay: A Simple Method to Reduce Catastrophic Forgetting in Target Incremental Visual NavigationXinting Li, Shizhou Zhang, Yue Lu … Yanning ZhangACM Cloud and Autonomic Computing Conference
  16. 2023PDF ↗
  17. 2023
    New Insights on Relieving Task-Recency Bias for Online Class Incremental LearningGuoqiang Liang, Zhao-Jie Chen, Zhaoqiang Chen … Yanning ZhangIEEE TCSVT
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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.