Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 4,574Sort Recent · Most cited
  1. 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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  2. 2025
    Federated Continual Learning: Concepts, Challenges, and SolutionsParisa Hamedi, Roozbeh Razavi‐Far, Ehsan HallajiNeurocomputing · University of New Brunswick · University of Windsor
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  3. 2025
    Adapt & Align: Continual Learning with Generative Models Latent Space AlignmentKamil Rafał Deja, Bartosz Cywiński, Jan Rybarczyk, T. P. TrzcinskiNeurocomputing · Warsaw University of Technology · IDEA of Development Foundation · +1
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  4. 2025
    Continual-MEGA: A Large-scale Benchmark for Generalizable Continual Anomaly DetectionGeonu Lee, Yujeong Oh, Geonhui Jang … Y. YooNeurocomputing
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  5. 2025
    Class Incremental Learning with probability dampening and cascaded gated classifierJary Pomponi, Alessio Devoto, Simone ScardapaneNeurocomputing · Sapienza University of Rome
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  6. 2025
    Minion Gated Recurrent Unit for Continual LearningAbdullah M. Zyarah, D. KudithipudiNeurocomputing
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times, and only papers with a PDF we can point you at, so every title opens the paper itself. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.