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.

6 papers of 8,653Sort Recent · Most cited
  1. 2020
    Drinking From a Firehose: Continual Learning With Web-Scale Natural LanguageHexiang Hu, Ozan Şener, Fei Sha, Vladlen KoltunTPAMI · University of Southern California · Intel (United States)
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  2. 2020
    Beneficial Perturbation Network for Designing General Adaptive Artificial Intelligence SystemsShixian Wen, Amanda Rios, Yunhao Ge, Laurent IttiTNNLS · University of Southern California
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  3. 2020
    Lifelong Learning Without a Task OracleAmanda Rios, Laurent IttiIEEE 32nd International Conference on Tools with Artifici… · University of Southern California
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  4. 2020
    Visually Grounded Continual Learning of Compositional SemanticsXisen Jin, Junyi Du, Arka Sadhu … Xiang RenarXiv · University of Southern California · California Southern University
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  5. 2020
    Regularize, Expand and Compress: NonExpansive Continual LearningJie Zhang, Junting Zhang, Shalini Ghosh … Yalin WangWACV · University of Southern California · Arizona State University · +1
  6. 2020
    Visually Grounded Continual Learning of Compositional PhrasesXisen Jin, Junyi Du, Arka Sadhu … Xiang RenEMNLP · University of Southern California · California Southern University · +1
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.