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.

6 papers of 8,653Sort Recent · Most cited
  1. 2025
    Jointly exploring client drift and catastrophic forgetting in dynamic learningNiklas Babendererde, Moritz Fuchs, Camila González … Anirban MukhopadhyayScientific Reports · Technische Universität Darmstadt · Stanford University · +1
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  2. 2020
    A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World LearningMartin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan RameshNeural Networks · Goethe University Frankfurt · Technische Universität Darmstadt · +1
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  3. 2022
    Return of the normal distribution: Flexible deep continual learning with variational auto-encodersYongwon Hong, Martin Mundt, Sungho Park … Hyeran ByunNeural Networks · Yonsei University · Technische Universität Darmstadt · +1
  4. 2022
    CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and ComparabilityMartin Mundt, Steven Lang, Quentin Delfosse, Kristian KerstingICLR · Technische Universität Darmstadt
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  5. 2021
    AdapterFusion: Non-Destructive Task Composition for Transfer LearningJonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé … Iryna GurevychEACL · Technische Universität Darmstadt · Supélec · +5
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  6. 2019
    Incremental Learning of an Open-Ended Collaborative Skill LibraryDorothea Koert, Susanne Trick, Marco Ewerton … Jan PetersInternational Journal of Humanoid Robotics · Technische Universität Darmstadt · Max Planck Institute for Intelligent Systems
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.