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. 2023
    Continual Learning: Forget-Free Winning Subnetworks for Video RepresentationsHaeyong Kang, Jaehong Yoon, Sung Ju Hwang, C. D. YooTPAMI
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  2. 2023
    Carpe diem: On the Evaluation of World Knowledge in Lifelong Language ModelsYujin Kim, Jaehong Yoon, Seonghyeon Ye … Se-young YunNAACL
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  3. 2023
    STELLA: Continual Audio-Video Pre-training with Spatio-Temporal Localized AlignmentJaewoo Lee, Jaehong Yoon, Wonjae Kim … Sung Ju HwangICML
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  4. 2023
    Continual Learners are Incremental Model GeneralizersJaehong Yoon, Sung Ju Hwang, Yu CaoICML
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  5. 2023
    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Dahyun Kim, Jaehong Yoon … C. D. YooICLR
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  6. 2023
    Forget-free Continual Learning with Soft-Winning SubNetworksHaeyong Kang, Jaehong Yoon, Sultan Rizky Hikmawan Madjid … C. D. YooarXiv
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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.