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.

6 papers of 8,653Sort Recent · Most cited
  1. 2025
    SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End DevicesZhengyi Zhong, Weidong Bao, Ji Wang … Wei Yang Bryan LimTNNLS · National University of Defense Technology · Sun Yat-sen University · +2
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  2. 2024
    Replay-Free Continual Low-Rank Adaptation with Dynamic MemoryHuancheng Chen, Jingtao Li, Weiming Zhuang … Lingjuan LyuarXiv
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  3. 2023
    TARGET: Federated Class-Continual Learning via Exemplar-Free DistillationJie Zhang, Chen Chen, Weiming Zhuang, Lingjuan LyuICCV · ETH Zurich · Sony Corporation (United States)
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  4. 2023
    Towards Adversarially Robust Continual LearningTao Bai, Chen Chen, Lingjuan Lyu … Bihan WenICASSP · Nanyang Technological University · Zhejiang University of Science and Technology · +2
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  5. 2023
    InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud RepresentationJiahua Dong, Yang Cong, Gan Sun … Ender KonukoğluTNNLS · Shenyang Institute of Automation · Chinese Academy of Sciences · +4
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  6. 2023
    DEJA VU: Continual Model Generalization For Unseen DomainsChenxi Liu, Lixu Wang, Lingjuan Lyu … Qi ZhuICLR
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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.