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. 2026
    Bridging Inter-Task Gap of Continual Self-Supervised Learning With External DataHaori Lu, Xusheng Cao, Linlan Huang … Xialei LiuIEEE TCSVT
  2. 2025
  3. 2025
    KAC: Kolmogorov-Arnold Classifier for Continual LearningYu-Song Hu, Zichen Liang, Fei Yang … Ming-Ming ChengCVPR
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  4. 2025
    Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental LearningXusheng Cao, Haori Lu, Linlan Huang … Ming-Ming ChengNeurIPS
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  5. 2025PDF ↗
  6. 2022
    Exemplar-Free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift CompensationMarco Cotogni, Fei Yang, Claudio Cusano … Joost van de WeijerInternational Journal of Computer Vision · University of Pavia · BGI Group (China) · +4
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  7. 2024
    Improving Continual Learning Performance and Efficiency with Auxiliary ClassifiersFilip Szatkowski, Yaoyue Zheng, Fei Yang … Joost van de WeijerICML
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  8. 2023
    ScrollNet: Dynamic Weight Importance for Continual LearningFei Yang, Kai Wang, Joost van de WeijerICCV
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  9. 2022
  10. 2021
    DANICE: Domain adaptation without forgetting in neural image compressionSudeep Katakol, Luis Herranz, Fei Yang, Marta MrakCVPR · University of Michigan · Umbo Computer Vision (United Kingdom) · +1
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  11. 2020PDF ↗
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.