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.

7 papers of 8,653Sort Recent · Most cited
  1. 2025
    From task-aware to task-agnostic parameter isolation for incremental learningÁlex Vicente, Paul Kirkland, Gaetano Di Caterina … Marc MasanaNeural Processing Letters · University of Strathclyde · United States Air Force Research Laboratory · +2
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  2. 2025
    Controlling ReRAM’s Switching Characteristics with Shadow Memory for Continual LearningSai Sukruth Bezugam, Tanmoy Bhattacharya, Horst Petschenig … Dmitri B. StrukovIEEE International Memory Workshop (IMW) · University of California, Santa Barbara · Graz University of Technology · +1
  3. 2024
    Continual Learning in the Presence of RepetitionHamed Hemati, Lorenzo Pellegrini, X.W. Duan … Gido M. van de VenNeural Networks · University of St.Gallen · University of Applied Sciences St. Gallen · +10
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  4. 2024
    Context association in pyramidal neurons through local synaptic plasticity in apical dendritesMaximilian Baronig, Robert LegensteinFrontiers · Graz University of Technology
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  5. 2022
    An Efficient Domain-Incremental Learning Approach to Drive in All Weather ConditionsM. Jehanzeb Mirza, Marc Masana, Horst Possegger, Horst BischofCVPR · Graz University of Technology · Christian Doppler Laboratory for Thermoelectricity · +1
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  6. 2020
    Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic RewiringThomas Limbacher, Robert LegensteinFrontiers · Graz University of Technology
  7. 2006
    Incremental learning of object detectors using a visual shape alphabetAndreas Opelt, Axel Pinz, Andrew ZissermanCVPR · Graz University of Technology · University of Oxford
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.