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.

19 papers of 11,817Sort Recent · Most cited
  1. 2026
    Multimodal Deepfake Detection with Quantum State Inspired Analytic Incremental Adaptability LearningJianbin Ye, Man Xiao, Bo Liu … Huai-Min WangInternational Conference on Multimedia Retrieval
  2. 2026PDF ↗
  3. 2026PDF ↗
  4. 2026
  5. 2025
  6. 2025
    Correlation-Based Knowledge Distillation in Exemplar-Free Class-Incremental LearningZijian Gao, Bo Liu, Kele Xu … Huai-Min WangIEEE Open Journal of the Computer Society
  7. 2024PDF ↗
  8. 2024PDF ↗
  9. 2024
    Continual Dialogue State Tracking via Reason-of-Select DistillationYujie Feng, Bo Liu, Xiaoyu Dong … A. LamACL
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  10. 2024
    KIF: Knowledge Identification and Fusion for Language Model Continual LearningYujie Feng, Xu Chu, Yongxin Xu … Xiao-Ming WuarXiv
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  11. 2024
  12. 2024PDF ↗
  13. 2023
    LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot LearningBo Liu, Yifeng Zhu, Chongkai Gao … Peter StoneNeurIPS
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  14. 2022
    Optical performance monitoring using lifelong learning with confrontational knowledge distillation in 7-core fiber for elastic optical networks.Xu Zhu, Bo Liu, Jianxin Ren … Yunyun ChenOptics Express · Nanjing University of Information Science and Technology
  15. 2022
    Continual Learning and Private UnlearningBo Liu, Qiang Liu, Peter StoneCoLLAs
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  16. 2022PDF ↗
  17. 2021
    Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksLemeng Wu, Bo Liu, Peter Stone, Qiang LiuNeurIPS · The University of Texas at Austin
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  18. 2021
    A Lifelong Learning Approach to Mobile Robot NavigationBo Liu, Xuesu Xiao, Peter StoneRA-L · The University of Texas at Austin · Sony Corporation (United States)
  19. 2020
    Lifelong NavigationBo Liu, Xuesu Xiao, Peter StonearXiv · The University of Texas at Austin
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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.