Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

18 papers of 8,653Sort Recent · Most cited
  1. 2026
    Online label aggregation with incomplete crowd responsesYuyang Liu, Haoyu Liu, Runze Wu … Changjie FanInformation Sciences · Chinese Academy of Medical Sciences & Peking Union Medical College · NetEase (China) · +1
  2. 2025
    Dynamic prompt allocation and tuning for continual test-time adaptationChaoran Cui, Yongrui Zhen, Shuai Gong … Yilong YinInformation Sciences · Shandong University of Finance and Economics · Shandong University
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  3. 2025
    HINT: Hypernetwork approach to training weight interval regions in continual learningPatryk Krukowski, Anna Bielawska, Kamil Książek … Przemysław SpurekInformation Sciences · Jagiellonian University · Narodowy Instytut Leków · +1
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  4. 2025
    PILOT: a pre-trained model-based continual learning toolboxHailong Sun, Dawei Zhou, De‐Chuan Zhan, Han-Jia YeInformation Sciences · Nanjing University
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  5. 2025
    ReFNet: Rehearsal-based graph lifelong learning with multi-resolution framelet graph neural networksMing Li, Xiaoyi Yang, Yuting Chen … Qintai HuInformation Sciences · Zhejiang Normal University · Chinese University of Hong Kong · +1
  6. 2024
    Hybrid rotation self-supervision and feature space normalization for class incremental learningWenyi Feng, Zhe Wang, Qian Zhang … Zhilin FuInformation Sciences · Qinghai University · East China University of Science and Technology
  7. 2024
  8. 2024
    Cross-Domain Continual Learning via CLAMPWeiwei Weng, Mahardhika Pratama, Jie Zhang … Savitha RamasamyInformation Sciences · Nanyang Technological University · University of South Australia · +1
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  9. 2024
    Few-Shot Class Incremental Learning via Robust Transformer ApproachNaeem Paeedeh, Naeem Paeedeh, Mahardhika Pratama … Ryszard KowalczykInformation Sciences · University of South Australia · Universitas Gadjah Mada · +2
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  10. 2024
    Bridging pre-trained models to continual learning: A hypernetwork based framework with parameter-efficient fine-tuning techniquesFengqian Ding, Chen Xu, Han Liu … Hongchao ZhouInformation Sciences · Shandong University
  11. 2023
    Learnware: small models do bigZhihua Zhou, Zhi-Hao TanInformation Sciences · Nanjing University
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  12. 2023
    Task-specific parameter decoupling for class incremental learningRunhang Chen, Xiao‐Yuan Jing, Fei Wu … Yaru HaoInformation Sciences · Wuhan University · Guangdong University of Petrochemical Technology · +2
  13. 2023
    PyCIL: a Python toolbox for class-incremental learningDa-Wei Zhou, Fuyun Wang, Han-Jia Ye, De‐Chuan ZhanInformation Sciences · Nanjing University
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  14. 2023
    Federated probability memory recall for federated continual learningZhe Wang, Yu Zhang, Xinlei Xu … Wenli DuInformation Sciences · East China University of Science and Technology
  15. 2022
    Communication-efficient federated continual learning for distributed learning system with Non-IID dataZhao Zhang, Yong Zhang, Da Guo … Xiaolin ZhuInformation Sciences · Beijing University of Posts and Telecommunications
  16. 2022
    Target layer regularization for continual learning using Cramer-Wold distanceMarcin Mazur, Łukasz Pustelnik, Szymon Knop … Przemysław SpurekInformation Sciences · Jagiellonian University
  17. 2022
    HLifeRL: A hierarchical lifelong reinforcement learning frameworkFan Ding, Fei ZhuInformation Sciences · Soochow University
  18. 2022
    Knowledge extraction and retention based continual learning by using convolutional autoencoder-based learning classifier systemMuhammad Irfan, Jiangbin Zheng, Muhammad Iqbal … Muhammad Hassan ArifInformation Sciences · Northwestern Polytechnical University · Higher Colleges of Technology · +1
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.