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.

15 papers of 8,653Sort Recent · Most cited
  1. 2022
    Continual Learning via Sequential Function-Space Variational InferenceTim G. J. Rudner, Freddie Bickford Smith, Qixuan Feng … Yarin GalICML
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  2. 2022
    Probabilistic Bilevel Coreset SelectionXiaofang Zhou, Renjie Pi, Weizhong Zhang … Tong ZhangICML
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  7. 2022
    Continual Learning with Guarantees via Weight Interval ConstraintsMaciej Wołczyk, Karol J. Piczak, Bartosz Wójcik … Przemysław SpurekICML
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  8. 2022
    StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering ModelsAdam Liška, Tomáš Kočiský, Elena Gribovskaya … Angeliki LazaridouICML
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  9. 2022
    Efficient Test-Time Model Adaptation without ForgettingShuaicheng Niu, Jiaxiang Wu, Yifan Zhang … Mingkui TanICML
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  11. 2022
    Forget-free Continual Learning with Winning SubnetworksHaeyong Kang, R. Mina, Sultan Rizky Hikmawan Madjid … C. YooICML
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  14. 2022
    Controlling Conditional Language Models without Catastrophic ForgettingTomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc DymetmanICML
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  15. 2022
    Wide Neural Networks Forget Less CatastrophicallySeyed Iman Mirzadeh, Arslan Chaudhry, Yin, Dong … Mehrdad FarajtabarICML · Google (United States)
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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.