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.

10 papers of 8,653Sort Recent · Most cited
  1. 2026
    Federated continual learning with joint diffusion-based generative replayYouhuizi Li, Yu Chen, Yiran Ma … Shuyuan HuApplied Soft Computing · Hangzhou Dianzi University
  2. 2026
  3. 2026
    Continual learning classification method with antigen-presenting cell region walking based on the artificial immune systemJia Liu, Zhinong Li, Dong Li … Xingwei SunApplied Soft Computing · Shenyang University of Technology · Aero Engine Corporation of China (China) · +2
  4. 2026
  5. 2025
    Continual learning with a predictive coding based classifierSenhui Qiu, Saugat Bhattacharyya, Damien Coyle, Shirin DoraApplied Soft Computing · University of Ulster · Intelligent Systems Research (United States) · +2
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  6. 2025
    Plastic Distillation and Local Class Augment for Federated Class Incremental LearningWenyi Feng, Jianqiang Huang, Wandong XueApplied Soft Computing · Qinghai University
  7. 2025
    A Dual-Channel Collaborative Transformer for continual learningHao Cai, Yizhe Wang, Yong Luo, Keming MaoApplied Soft Computing · Northeastern University · Dalian University of Technology
  8. 2024
    Continual compression model for online continual learningFei Ye, Adrian G. BorşApplied Soft Computing · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +1
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  9. 2021
    Adaptive online incremental learning for evolving data streamsSisi Zhang, Jian–wei Liu, Xin ZuoApplied Soft Computing · China University of Petroleum, Beijing
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  10. 2020
    Continual learning classification method with new labeled data based on the artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunApplied Soft Computing · Hong Kong University of Science and Technology · Changzhou University · +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.