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.

4 papers of 8,653Sort Recent · Most cited
  1. 2022
    CL-Cross VQA: A Continual Learning Benchmark for Cross-Domain Visual Question AnsweringYao Zhang, Haokun Chen, Ahmed Frikha … Volker TrespWACV · LMU Klinikum · Ludwig-Maximilians-Universität München · +1
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  2. 2022
    Exact learning dynamics of deep linear networks with prior knowledgeClémentine Dominé, Lukas Braun, James E. Fitzgerald, Andrew SaxeNeurIPS · Gatsby Computational Neuroscience Unit · University College London · +4
  3. 2022
    Same State, Different Task: Continual Reinforcement Learning without InterferenceSamuel Kessler, Jack Parker-Holder, Philip Ball … Stephen RobertsAAAI · University of Oxford
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  4. 2022
    Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental LearningYujun Shi, Kuangqi Zhou, Jian Liang … Vincent Y. F. TanCVPR · National University of Singapore · Chinese Academy of Sciences · +1
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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. 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.