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.

7 papers of 11,817Sort Recent · Most cited
  1. 2026
    Bridging Inter-Task Gap of Continual Self-Supervised Learning With External DataHaori Lu, Xusheng Cao, Linlan Huang … Xialei LiuIEEE TCSVT
  2. 2025
    Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental LearningXusheng Cao, Haori Lu, Linlan Huang … Ming-Ming ChengNeurIPS
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  3. 2025PDF ↗
  4. 2025
    Class Incremental Learning for Image Classification With Out-of-Distribution Task IdentificationXusheng Cao, Haori Lu, Xialei Liu, Ming-Ming ChengIEEE Trans. Multimedia
  5. 2024PDF ↗
  6. 2024
    Generative Multi-modal Models are Good Class-Incremental LearnersXusheng Cao, Haori Lu, Linlan Huang … Ming-Ming ChengCVPR
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  7. 2023
    Class Incremental Learning with Pre-trained Vision-Language ModelsXialei Liu, Xusheng Cao, Haori Lu … Ming-Ming ChengarXiv
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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. 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.