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.

10 papers of 11,817Sort Recent · Most cited
  1. 2024
    Dynamic prompt allocation and tuning for continual test-time adaptationChaoran Cui, Yongrui Zhen, Shuai Gong … Yilong YinInformation Sciences
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  2. 2024
    An adaptive feature extraction and fusion method for few-shot target classificationPing Li, Chenxing Jia, Shuo Wang … Lei LuInformation Sciences
  3. 2024
    Class-Incremental Learning for Enhanced Food RecognitionYen Thi Hong Tran, P. Nguyen, Hung Nguyen, Khanh-Duy NguyenInformation Sciences
  4. 2024
    Hybrid rotation self-supervision and feature space normalization for class incremental learningWenyi Feng, Zhe Wang, Qian Zhang … Zhiling FuInformation Sciences
  5. 2024
  6. 2024
    UAS Visual Navigation in Large and Unseen Environments via a Meta AgentYu-Ci Han, C. Toth, Alper YilmazInformation Sciences
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  7. 2024
    HINT: Hypernetwork approach to training weight interval regions in continual learningPatryk Krukowski, Anna Bielawska, Kamil Książek … P. SpurekInformation Sciences
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  8. 2024
    Few-Shot Class Incremental Learning via Robust Transformer ApproachNaeem Paeedeh, Mahardhika Pratama, S. Wibirama … Ryszard KowalczykInformation Sciences
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  9. 2024
  10. 2024
    Cross-Domain Continual Learning via CLAMPWeiwei Weng, Mahardhika Pratama, Jie Zhang … R. SavithaInformation Sciences
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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.