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.

12 papers of 8,653Sort Recent · Most cited
  1. 2022
    On Continual Model Refinement in Out-of-Distribution Data StreamsBill Lin, Sida Wang, Xi Victoria Lin … Wen-tau YihACL
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  2. 2022PDF ↗
  3. 2022
    ConTinTin: Continual Learning from Task InstructionsWenpeng Yin, Jia Li, Caiming XiongACL
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  4. 2022
    Continual Prompt Tuning for Dialog State TrackingQi Zhu, Bing Li, Fei Mi … Minlie HuangACL
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  5. 2022
    ELLE: Efficient Lifelong Pre-training for Emerging DataYujia Qin, Jiajie Zhang, Yankai Lin … Jie ZhouACL
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  9. 2022
    TimeLMs: Diachronic Language Models from TwitterDaniel Loureiro, Francesco Barbieri, Leonardo Neves … Jose Camacho-colladosACL · Universidade do Porto · Snap (United States) · +2
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  10. 2022
    Learn and Review: Enhancing Continual Named Entity Recognition via Reviewing Synthetic SamplesYu Xia, Quan Wang, Yajuan Lyu … Dai DaiACL · Peking University · Baidu (China)
  11. 2022
    Few-Shot Class-Incremental Learning for Named Entity RecognitionRui Wang, Tong Yu, Handong Zhao … Ricardo HenaoACL · Duke University · Adobe Systems (United States)
  12. 2022
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.