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.

3 papers of 8,653Sort Recent · Most cited
  1. 2025
    Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual LearningXiaoming Qi, Jingyang Zhang, Huazhu Fu … Yueming JinInformation Processing in Medical Imaging
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  2. 2025
    Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for FCLXiaoming Qi, Jingyang Zhang, Huazhu Fu … Yueming JinarXiv
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  3. 2024
    Learning Task-Specific Initialization for Effective Federated Continual Fine-Tuning of Foundation Model AdaptersDanni Peng, Yuan Wang, Huazhu Fu … Rick Siow Mong GohIEEE Conference on Artificial Intelligence (CAI) · Agency for Science, Technology and Research · Institute of High Performance Computing
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.