Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

5 papers of 6,984Sort Recent · Most cited
  1. 2025
    Rethinking Obscured Sub-Optimality in Analytic Learning for Exemplar-Free Class-Incremental LearningZijian Gao, Kele Xu, Xingxing Zhang … Huaimin WangIEEE TCSVT · National University of Defense Technology · Tsinghua University · +1
  2. 2025
    Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental LearningZijian Gao, Wangwang Jia, Xingxing Zhang … Huaimin WangCVPR · National University of Defense Technology · Tsinghua University
  3. 2025
    Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental LearningZijian Gao, Shanhao Han, Xingxing Zhang … Huaimin WangAAAI · National University of Defense Technology · Tsinghua University
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  4. 2025
    Correlation-Based Knowledge Distillation in Exemplar-Free Class-Incremental LearningZijian Gao, Bo Liu, Kele Xu … Huaimin WangIEEE Open Journal of the Computer Society · National University of Defense Technology · Academy of Military Medical Sciences
  5. 2024
    Less confidence, less forgetting: Learning with a humbler teacher in exemplar-free Class-Incremental learningZijian Gao, Kele Xu, Huiping Zhuang … Huaimin WangNeural Networks · National University of Defense Technology · South China University of Technology · +2
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.