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.

15 papers of 11,817Sort Recent · Most cited
  1. 2025
    Continual Learning for Generative AI: From LLMs to MLLMs and BeyondHaiyang Guo, Fanhu Zeng, Fei Zhu … Cheng-Lin LiuarXiv
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  2. 2025
    LLaVA-c: Continual Improved Visual Instruction TuningWenzhuo Liu, Fei Zhu, Haiyang Guo … Cheng-Lin LiuarXiv
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  3. 2025
    Federated Continual Instruction TuningHaiyang Guo, Fanhu Zeng, Fei Zhu … Cheng-Lin LiuICCV
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  4. 2024PDF ↗
  5. 2024
    RCL: Reliable Continual Learning for Unified Failure DetectionFei Zhu, Zhen Cheng, Xu-Yao Zhang … Zhao-kui ZhangCVPR
  6. 2024
    Large-scale continual learning for ancient Chinese character recognitionYue Xu, Xu-Yao Zhang, Zhao-kui Zhang, Cheng-Lin LiuPattern Recognition
  7. 2024PDF ↗
  8. 2024PDF ↗
  9. 2024
    Open-world Machine Learning: A Review and New OutlooksFei Zhu, Shijie Ma, Zhen Cheng … Cheng-Lin LiuarXiv
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  10. 2024
    PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental LearningHaiyang Guo, Fei Zhu, Wenzhuo Liu … Cheng-Lin LiuECCV
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  11. 2024
  12. 2024
    Federated Class-Incremental Learning with Prototype Guided TransformerHaiyang Guo, Fei Zhu, Wenzhuo Liu … Cheng-Lin LiuarXiv
  13. 2023
    Class Incremental Learning with Self-Supervised Pre-Training and Prototype LearningWenzhuo Liu, Xin-Jian Wu, Fei Zhu … Cheng-Lin LiuPattern Recognition
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  14. 2023
    Imitating the oracle: Towards calibrated model for class incremental learningFei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin LiuNeural Networks
  15. 2021
    Class-Incremental Learning via Dual AugmentationFei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin LiuNeurIPS
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.