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.

3 papers of 8,653Sort Recent · Most cited
  1. 2026
    AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental LearningPengxiang Wang, Hongbo Bo, Jun Hong … Kedian MuSpringer LNCS · Peking University · University of Bristol · +2
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  2. 2022
    Ego-graph Replay based Continual Learning for Misinformation Engagement PredictionHongbo Bo, Ryan McConville, Jun Hong, Weiru LiuIJCNN · University of Bristol · University of the West of England
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  3. 2021
    Class-incremental Learning using a Sequence of Partial Implicitly Regularized ClassifiersSobirdzhon Bobiev, Albina Khusainova, Adil Khan, S. M. Ahsan Kazmi... International Florida Artificial Intelligence Researc… · Innopolis University · University of the West of England
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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.