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.

3 papers of 11,817Sort Recent · Most cited
  1. 2022
    Do Pre-trained Models Benefit Equally in Continual Learning?Kuan-Ying Lee, Yuanyi Zhong, Yu-Xiong WangWACV · University of Illinois Urbana-Champaign
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  2. 2022
    Continual‐learning‐based framework for structural damage recognitionJiangpeng Shu, Wei Ding, Jiawei Zhang … Yuanfeng DuanStructural Control and Health Monitoring · Zhejiang University · University of Illinois Urbana-Champaign · +1
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  3. 2022
    Learning Representations for New Sound Classes With Continual Self-Supervised LearningZhepei Wang, Cem Subakan, Xilin Jiang … Paris SmaragdisIEEE Signal Processing Letters · University of Illinois Urbana-Champaign · Concordia University · +2
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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.