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.

5 papers of 8,653Sort Recent · Most cited
  1. 2021
    Same State, Different Task: Continual Reinforcement Learning without InterferenceSamuel Kessler, Jack Parker-Holder, Philip Ball … Stephen RobertsAAAI · University of Oxford
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  2. 2021
    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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  3. 2021
    An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation LearningSamuel Kessler, Bethan Thomas, Salah KaroutICASSP · University of Oxford · Huawei Technologies (United Kingdom)
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  4. 2021
    Continual Learning in the Teacher-Student Setup: Impact of Task SimilaritySebastian Lee, Sebastian Goldt, Andrew SaxeICML · Microsoft Research (United Kingdom) · Scuola Internazionale Superiore di Studi Avanzati · +1
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  5. 2021
    Sustainable Artificial Intelligence through Continual LearningAndrea Cossu, Marta Ziosi, Vincenzo LomonacoInternational Conference on AI for People: Towards Sustai… · University of Pisa · Scuola Normale Superiore · +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. 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.