Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 6,984Sort Recent · Most cited
  1. 2026
    Coresets are more than replay: a data-centric view of continual learningElif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin VanschorenNeural Computing and Applications · Eindhoven University of Technology
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  2. 2026
    Pruned Adaptation Modules: A Simple yet Strong Baseline for Continual Foundation ModelsElif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin VanschorenarXiv
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  3. 2026
    Unlocking [CLS] Features for Continual Post-TrainingMurat Onur Yildirim, Elif Ceren Gok Yildirim, Joaquin VanschorenTMLR
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  4. 2024
    Continual Learning on a Data DietElif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin VanschorenarXiv
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  5. 2024
    Self-Regulated Neurogenesis for Online Data-Incremental LearningMurat Onur Yildirim, Elif Ceren Gok Yildirim, Decebal Constantin Mocanu, Joaquin VanschorenarXiv
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  6. 2023
    Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model UpdatesMurat Onur Yildirim, Elif Ceren Gok Yildirim, Ghada Sokar … Joaquin VanschorenCPAL
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  7. 2023
    AdaCL: Adaptive Continual LearningElif Ceren Gok Yildirim, Murat Onur Yildirim, Mert Kilickaya, Joaquin VanschorenCLAI Unconf
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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. 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.