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. 2024
  2. 2023
    Continual Learning in the Presence of Spurious CorrelationDonggyu Lee, Sangwon Jung, Taesup MoonarXiv
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  3. 2023
    Issues for Continual Learning in the Presence of Dataset BiasDonggyu Lee, Sangwon Jung, Taesup MoonAAAI
  4. 2022
    Dataset Condensation with Contrastive SignalsSaehyung Lee, Sanghyuk Chun, Sangwon Jung … Sungroh YoonICML
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  5. 2020
    Continual Learning with Node-Importance based Adaptive Group Sparse RegularizationSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup MoonNeurIPS · Sungkyunkwan University
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  6. 2020
    Adaptive Group Sparse Regularization for Continual LearningSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup MoonarXiv
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.