Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

9 papers of 11,817Sort Recent · Most cited
  1. 2026
    Self-supervised prototype alignment and aggregation for few-shot class-incremental infrared target recognitionDi Liu, Yan Zhang, Zhiguang Shi … Ruo-Bin GaoOptics & Laser Technology
  2. 2026
    Few-shot class-incremental infrared target recognition via contrastive self-supervised subspace classifierDi Liu, Yan Zhang, Zhiguang Shi … Feng LingOptics & Laser Technology
  3. 2026
    Flow-Kansformer: Predicting Gas–Liquid Flow Rate With Hybrid KAN-Enhanced TransformerHaoxiang Tang, Yan Zhang, Lin Chen … Yi LiIEEE Transactions
  4. 2025
    Multiresolution representation of distribution network triangular mesh based on incremental learning algorithm of power operation unbalanced big dataYan Zhang, Botao Fan, Junxiang Duan … Jie LiuInternational Conference on Electrical Engineering and Sm…
  5. 2025
    RehearMixup: Improving rehearsal-based continual learningYan Zhang, Kaiyuan Qi, Dong Wu … Yilong YinNeurocomputing
  6. 2025
    FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation SteeringYichen Li, Zhiting Fan, Ruizhe Chen … Zuozhu LiuACL
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  7. 2025
    Towards Macro-AUC Oriented Imbalanced Multi-Label Continual LearningYan Zhang, Guoqiang Wu, Bingzheng Wang … Yilong YinAAAI
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  8. 2024
  9. 2020
    Disentangle-based Continual Graph Representation LearningXiaoyu Kou, Yankai Lin, Shaobo Liu … Yan ZhangEMNLP · Peking University · Tencent (China)
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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.