Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2025PDF ↗
  3. 2025
  4. 2024PDF ↗
  5. 2024
    Solving the Catastrophic Forgetting Problem in Generalized Category DiscoveryXinzi Cao, Xiawu Zheng, Guanhong Wang … Yonghong TianCVPR
    PDF ↗
  6. 2022
    Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental LearningXialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov … Ming‐Ming ChengCVPR · Nankai University · University of Florence · +1
    PDF ↗
  7. 2024
  8. 2023
    Masked Autoencoders are Efficient Class Incremental LearnersJiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov … Mingg-Ming ChengICCV
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  9. 2022
    Long-Tailed Class Incremental LearningXialei Liu, Yusong Hu, Xusheng Cao … Ming‐Ming ChengECCV
    PDF ↗
  10. 2022
    Robust Saliency Guidance for Data-free Class Incremental LearningXialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov … Ming-Ming ChengarXiv
  11. 2019
    Better Knowledge Retention through Metric LearningKe Li, Shichong Peng, Kailas Vodrahalli, Jitendra MalikarXiv
    PDF ↗
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.