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.

7 papers of 6,984Sort Recent · Most cited
  1. 2026
    Negative-weighted knowledge distillation regularized graph convolutional network for multi-label class-incremental learningKaile Du, Junzhou Xie, Fan Lyu … Guangcan LiuPattern Recognition · Southeast University · Institute of Automation · +1
  2. 2026
    GAIN: Global-Atomic INteraction Graph for Few-Shot Class-Incremental LearningFan Lyu, Linglan Zhao, Changli Liu … Liang WangIEEE TCSVT · Chinese Academy of Sciences · Institute of Automation · +6
  3. 2026
    Constructing Enhanced Mutual Information for Online Class-Incremental LearningHuan Zhang, Fan Lyu, Shenghua Fan … Dingwen WangIEEE Trans. Multimedia · Wuhan University · Institute of Automation
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  4. 2025
    Mitigating Catastrophic Forgetting in Online Continual Learning With Dual-Margin Contrastive ReplayFan Lyu, Gongbo Cheng, Daofeng Liu … Liang WangIEEE TCSVT · Chinese Academy of Sciences · Institute of Automation · +2
  5. 2025
    Beyond Background Shift: Rethinking Instance Replay in Continual Semantic SegmentationHongmei Yin, Tingliang Feng, Fan Lyu … Liang WanCVPR · Tianjin University · Institute of Automation
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  6. 2025
    Few-Shot Class-Incremental Learning via Asymmetric Supervised Contrastive LearningDuo Liu, Linglan Zhao, Zhongqiang Zhang … Liang WangIEEE TCSVT · Shanghai Jiao Tong University · Tencent (China) · +4
  7. 2024
    Towards Long-Term Remembering in Federated Continual LearningZiqin Zhao, Fan Lyu, Linyan Li … Li SunCognitive Computation · Suzhou University of Science and Technology · Institute of Automation · +3
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.