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.

6 papers of 11,817Sort Recent · Most cited
  1. 2025
    Hybrid Ensemble Framework for Imbalanced Data Streams With Concept DriftMianfen Lin, Zhiwen Yu, Kaixiang Yang, C. L. Philip ChenIEEE Transactions
  2. 2025
    Addressing Client Drift in Federated Learning via Class-Prototype Similarity Distillation and Adaptive MaskYu-bao Yan, Chun-Mei Feng, Mang Ye … C. L. Philip ChenIEEE Trans. Cybernetics
  3. 2025
    Dynamic Broad Metric LearningXiaoman Hu, C. L. Philip Chen, Tong ZhangIEEE TAI
  4. 2025
  5. 2025
    SGB-Net: Scalable Graph Broad NetworkYue-Bin Xu, C. L. Philip Chen, Meng-Qi Wu, Tong ZhangTNNLS
  6. 2025
    Broad learning system based on fractional order optimizationDan Zhang, Tong Zhang, Zhang Tao, C. L. Philip ChenNeural Networks
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.