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. 2022
    Streaming Graph Neural Networks with Generative ReplayJunshan Wang, Wenhao Zhu, Guojie Song, Liang WangKDD · Alibaba Group (China) · Peking University
  2. 2022
    Geometer: Graph Few-Shot Class-Incremental Learning via Prototype RepresentationBin Lü, Xiaoying Gan, Lina Yang … Xinbing WangKDD · Shanghai Jiao Tong University
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  3. 2022
    Adaptive Fairness-Aware Online Meta-Learning for Changing EnvironmentsChen Zhao, Feng Mi, Xintao Wu … Feng ChenKDD · The University of Texas at Dallas · University of Arkansas at Fayetteville
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  4. 2022
    Preventing Catastrophic Forgetting in Continual Learning of New Natural Language TasksSudipta Kar, Giuseppe Castellucci, Simone Filice … Oleg RokhlenkoKDD · Amazon (United States)
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  5. 2022
    ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production ScaleGopinath Chennupati, Milind Rao, Gurpreet Chadha … Pankaj SitpureKDD · Amazon (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.