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
    Singular Value Fine-Tuning for Few-Shot Class-Incremental LearningZhi-Wu Wang, Yichen Wu, Renzhen Wang … Deyu MengIEEE TCSVT
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  2. 2025
    Adaptation of Agentic AIPengcheng Jiang, Jia-Cheng Lin, Zhiyi Shi … Jiawei HanarXiv
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  3. 2025PDF ↗
  4. 2025PDF ↗
  5. 2025
    SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental LearningYichen Wu, Hongming Piao, Long-Kai Huang … Ying WeiICLR
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  6. 2024
    Continual Learning for Segment Anything Model AdaptationJinglong Yang, Yichen Wu, Jun Cen … Jianguo ZhangarXiv
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  7. 2024PDF ↗
  8. 2024
  9. 2024
    Federated Continual Learning via Prompt-based Dual Knowledge TransferHongming Piao, Yichen Wu, Dapeng Wu, Ying WeiICML
  10. 2024
  11. 2023
    CBA: Improving Online Continual Learning via Continual Bias AdaptorQuanziang Wang, Renzhen Wang, Yichen Wu … Deyu MengICCV
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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.