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. 2025PDF ↗
  2. 2025
    CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained ModelsShengzhuang Chen, Y. Liao, Xiaoxiao Sun … Ying WeiICLR
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  3. 2025PDF ↗
  4. 2025
    SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental LearningYichen Wu, Hongming Piao, Long-Kai Huang … Ying WeiICLR
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  5. 2024
    Refine Large Language Model Fine-tuning via Instruction VectorGangwei Jiang, Zhaoyi Li, Defu Lian, Ying WeiarXiv
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  6. 2024
  7. 2024
    Federated Continual Learning via Prompt-based Dual Knowledge TransferHongming Piao, Yichen Wu, Dapeng Wu, Ying WeiICML
  8. 2024
  9. 2023
    Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation FrameworkWeiduo Liao, Ying Wei, Mingcheng Jiang … H. IshibuchiNeurIPS
  10. 2019
    Hierarchically Structured Meta-learningHuaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui LiICML · Pennsylvania State University
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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.