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.

9 papers of 8,653Sort Recent · Most cited
  1. 2025
    Merging Versus Separating Replay Samples in Continual LearningAndrii KrutsyloSpringer LNCS · Institute of Computer Science · Polish Academy of Sciences
  2. 2025
    Continually Learn to Map Visual Concepts to Large Language Models in Resource-constrained EnvironmentsClea Rebillard, Julio Hurtado, Andrii Krutsylo … Vincenzo LomonacoNeurocomputing · Institut Polytechnique de Bordeaux · University of Warwick · +3
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  3. 2025PDF ↗
  4. 2024
    Evaluating Knowledge Retention in Continual LearningAndrii KrutsyloACM/SIGAPP Symposium on Applied Computing · Institute of Computer Science · Polish Academy of Sciences
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  5. 2024
    The Inter-batch Diversity of Samples in Experience Replay for Continual LearningAndrii KrutsyloAAAI · Czech Academy of Sciences, Institute of Computer Science · Polish Academy of Sciences
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  6. 2024
    Batch Sampling for Experience ReplayAndrii KrutsyloJoint International Conference on Data Science & Mana… · Institute of Computer Science · Polish Academy of Sciences
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  7. 2022
    Hebbian Continual Representation LearningPaweł Morawiecki, Andrii Krutsylo, Maciej Wołczyk, Marek ŚmiejaJournal of the Association for Information Systems
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  8. 2022
    Diverse Memory for Experience Replay in Continual LearningAndrii Krutsylo, Paweł MorawieckiESANN 2022 proceedings · Institute of Computer Science · Polish Academy of Sciences
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  9. 2021
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.