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.

7 papers of 8,653Sort Recent · Most cited
  1. 2025
    Meta-Continual Learning of Neural FieldsSeongyoun Woo, Yun, Junhyeog, Gunhee KimICLR
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  2. 2023
    When Meta-Learning Meets Online and Continual Learning: A SurveyJaehyeon Son, Soochan Lee, Gunhee KimTPAMI · Seoul National University · LG (South Korea)
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  3. 2024
    Learning to Continually Learn with the Bayesian PrincipleSoochan Lee, Hyeonseong Jeon, Jaehyeon Son, Gunhee KimICML
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  4. 2023
    Recasting Continual Learning as Sequence ModelingSoochan Lee, Jaehyeon Son, Gunhee KimNeurIPS
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  5. 2021
    Continual Learning on Noisy Data Streams via Self-Purified ReplayChris Dongjoo Kim, Jinseo Jeong, Sangwoo Moon, Gunhee KimICCV · Seoul National University
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  6. 2020
    A Neural Dirichlet Process Mixture Model for Task-Free Continual LearningSoochan Lee, Junsoo Ha, Dongsu Zhang, Gunhee KimICLR
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  7. 2020
    Imbalanced Continual Learning with Partitioning Reservoir SamplingChris Dongjoo Kim, Jinseo Jeong, Gunhee KimSpringer LNCS · Seoul National University
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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.