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.

5 papers of 8,653Sort Recent · Most cited
  1. 2023
    Continual Learning: Forget-Free Winning Subnetworks for Video RepresentationsHaeyong Kang, Jaehong Yoon, Sung Ju Hwang, Chang D. YooTPAMI · Korea Advanced Institute of Science and Technology
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  2. 2024
    Soft-TransFormers for Continual LearningKang, Haeyong, Chang D. YooarXiv
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  3. 2023
    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Jaehong Yoon, DaHyun Kim … Chang D. YooICLR
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  4. 2023
    Forget-free Continual Learning with Soft-Winning SubNetworksHaeyong Kang, Jaehong Yoon, Sultan Rizky Madjid … Chang D. YooarXiv
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  5. 2022
    On the Soft-Subnetwork for Few-shot Class Incremental LearningHaeyong Kang, Jaehong Yoon, Sultan Rizky Hikmawan Madjid … Chang D. YooICLR
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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.