Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 8,653Sort Recent · Most cited
  1. 2026
    Singular Value Fine-Tuning for Few-Shot Class-Incremental LearningZhiwu Wang, Yichen Wu, Renzhen Wang … Deyu MengIEEE TCSVT · Xi'an Jiaotong University · City University of Hong Kong
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  2. 2024
    Dual-CBA: Improving Online Continual Learning via Dual Continual Bias Adaptors From a Bi-level Optimization PerspectiveHong Wang, Renzhen Wang, Yichen Wu … Deyu MengTPAMI · Xi'an Jiaotong University · Harvard University · +1
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  3. 2026
    Diagnosing BN discrepancy in rehearsal-based class incremental learningMinghao Zhou, Quanziang Wang, Renzhen Wang … Deyu MengInternational Journal of Machine Learning and Cybernetics
  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. 2025
  7. 2021
    Relational Experience Replay: Continual Learning by Adaptively Tuning Task-Wise RelationshipQuanziang Wang, Renzhen Wang, Yuexiang Li … Deyu MengIEEE Trans. Multimedia · Xi'an Jiaotong University · Tencent (China) · +1
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  8. 2024
  9. 2023
    CBA: Improving Online Continual Learning via Continual Bias AdaptorQuanziang Wang, Renzhen Wang, Yichen Wu … Deyu MengICCV · Xi'an Jiaotong University · City University of Hong Kong · +2
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  10. 2022
    Diagnosing Batch Normalization in Class Incremental LearningMinghao Zhou, Quanziang Wang, Jun Shu … Deyu MengarXiv
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  11. 2021
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.