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.

31 papers of 11,817Sort Recent · Most cited
  1. 2025
    Towards understanding memory buffer based continual learningGuodong Zheng, Peng Wang, Tao Sun, Li ShenNeural Networks
  2. 2025
    Dual-modality adaptation in vision-language models for continual learningJiayang Zeng, Wentao Zhang, Kanghao Chen … Ruixuan WangNeural Networks
  3. 2025
  4. 2025
  5. 2025
    CSCL: Bridging the plasticity-stability gap in continuous supervised contrastive learningYi Xiong, Li-Qi Xiang, Qianyue Cao … Xuehai ZhouNeural Networks
  6. 2025
    Continual learning: A systematic literature reviewQinwen Yang, Li-Yuan Wang, Joerg Wicker, Gillian DobbieNeural Networks
  7. 2025
    C3GAN: A brain-inspired memory consolidation for class-incremental learningLin Xiong, Tao Wang, Fuqing Zhang … Hailing XiongNeural Networks
  8. 2025
    Rethinking softmax in incremental learningZheng Zhai, Jiali Zhang, Haiyu Wang … Qiang SunNeural Networks
  9. 2025
    PKI: Prior knowledge-infused neural network for few-shot class-incremental learningKexin Bao, Fanzhao Lin, Zichen Wang … Shiming GeNeural Networks
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  10. 2025
  11. 2025
  12. 2025
    Multiple semantic prompt for rehearsal-free continual learningJunwei Chen, Zhenyu Zhang, De-Peng Li, Zhi-Gang ZengNeural Networks
  13. 2025
  14. 2025
    Prototypes as Anchors: Tackling Unseen Noise for online continual learningShao-Yuan Li, Yuxiang Zheng, Sheng-Jun Huang … Kang-Kan WangNeural Networks
  15. 2025
    Supervised contrastive learning with prototype distillation for data incremental learningSuorong Yang, Tianyue Zhang, Zhiming Xu … Jian ZhaoNeural Networks
  16. 2025
    Neuromimetic metaplasticity for adaptive continual learning without catastrophic forgettingSuhee Cho, Hyeonsu Lee, Seungdae Baek, Se-Bum PaikNeural Networks
  17. 2025
    Flashbacks to Harmonize Stability and Plasticity in Continual LearningLeila Mahmoodi, Peyman Moghadam, Munawar Hayat … Mehrtash HarandiNeural Networks
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  18. 2025
    Information-Theoretic Complementary Prompts for Improved Continual Text ClassificationDuzhen Zhang, Yong Ren, Chen-Xing Li … Tie-Lin ZhangNeural Networks
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  19. 2025
    Prompt-Enhanced: Leveraging language representation for prompt continual learning.Wei Li, De-Zhi Li, Shitong Shao … Zhen LeiNeural Networks
  20. 2025
    DeepART: Deep gradient-free local learning with adaptive resonanceSasha A. Petrenko, Leonardo Enzo Brito da Silva, D. C. WunschNeural Networks
  21. 2025
    Exploration and exploitation in continual learningKiseong Hong, Hyundong Jin, Sungho Suh, Eunwoo KimNeural Networks
  22. 2025
  23. 2025
    Broad learning system based on fractional order optimizationDan Zhang, Tong Zhang, Zhang Tao, C. L. Philip ChenNeural Networks
  24. 2025
  25. 2025
    Generative Binary Memory: Pseudo-Replay Class-Incremental Learning on Binarized EmbeddingsYanis Basso-Bert, W. Guicquero, A. Molnos … Antoine DupretNeural Networks
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  26. 2025
    Using samples with label noise for robust continual learningHongyi Nie, Shiqi Fan, Yang Liu … Zhen WangNeural Networks
  27. 2025
    L3Net: Localized and Layered Reparameterization for incremental learningXuandi Luo, Huaidong Zhang, Yi Xie … Shengfeng HeNeural Networks
  28. 2025
    PVBF: A Framework for Mitigating Parameter Variation Imbalance in Online Continual LearningZe-Lin Tao, Hao Deng, Mingqing Liu … Shengjie ZhaoNeural Networks
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  29. 2025
    DuPt: Rehearsal-based continual learning with dual promptsShengqin Jiang, Dao-Long Zhang, Fengna Cheng … Qingshan LiuNeural Networks
  30. 2025
  31. 2025
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.