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. 2026
    AdaptCMVC++: Robust and Flexible Adaptation to Incremental Views in Continual Multi-view Clustering.Jing Wang, Songhe Feng, Jiacheng Li … Michael KampffmeyerTPAMI · Beijing Foreign Studies University · Beijing Jiaotong University · +2
  2. 2025
    AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view ClusteringJing Wang, Songhe Feng, Kristoffer Wickstrøm, Michael KampffmeyerCVPR · Beijing Jiaotong University · UiT The Arctic University of Norway
  3. 2021
    Learning to Transfer with von Neumann Conditional DivergenceAmmar Shaker, Shujian Yu, Daniel Oñoro-RubioAAAI · Sharp Laboratories of Europe (United Kingdom) · Centre for Arctic Gas Hydrate, Environment and Climate · +2
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  4. 2020
    Modular-Relatedness for Continual LearningAmmar Shaker, Francesco Alesiani, Shujian YuSpringer LNCS · UiT The Arctic University of Norway
    PDF ↗
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.