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.

4 papers of 8,653Sort Recent · Most cited
  1. 2025
    Learning After Model DeploymentDerda Kaymak, Gyuhak Kim, Tomoya Kaichi … Bing LiuFrontiers · University of Illinois Chicago · Accenture (United States) · +1
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  2. 2024
    Multi-Modal Continual Pre-Training For Audio EncodersGyuhak Kim, Ho-Hsiang Wu, Luca Bondi, Bing LiuICASSP · University of Illinois Chicago · Robert Bosch (United States)
  3. 2022
    Continual Learning Based on OOD Detection and Task MaskingGyuhak Kim, Sepideh Esmaeilpour, Changnan Xiao, Bing LiuCVPR · University of Illinois Chicago
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  4. 2022
    Partially Relaxed Masks for Knowledge Transfer Without Forgetting in Continual LearningTatsuya Konishi, Mori Kurokawa, Chihiro Ono … Bing LiuSpringer LNCS · KDDI Research (Japan) · University of Illinois Chicago
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.