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
  2. 2026
    Incomplete cross-modality class-incremental learning in visible-thermal recognitionXinjie Yao, Yanxian Bi, Yu Wang … Qinghua HuPattern Recognition
  3. 2026
    Topology-aware Knowledge Preservation for Class-Incremental LearningHan Zang, Yongfeng Dong, L. Li … Yu WangAAAI
  4. 2026
    Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA ModelsLiang-Zhi Shi, Shuaihang Chen, Feng Gao … Yu WangarXiv
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  5. 2026
  6. 2025
  7. 2025
    Visible-thermal cross-modality class-incremental learningXinjie Yao, Ying-Xue Wang, Yu Wang … Wanyu LinExpert Systems with Applications
  8. 2025
    Multi-View Fusion Graph Attention Network for Multilabel Class Incremental LearningAnhui Tan, Yu Wang, Wei-Zhi Wu … Ji-Ye LiangInformation Fusion
  9. 2025PDF ↗
  10. 2025
    Adaptive Broad Learning Network for Lightweight Multi-Dimensional Spectrum PredictionNiancong Ji, Yi-Bin Zhang, Yong-An Guo … Hikmet SariIEEE Transactions
  11. 2025PDF ↗
  12. 2024
    Self-Updatable Large Language Models by Integrating Context into Model ParametersYu Wang, Xinshuang Liu, Xiusi Chen … Julian J. McAuleyICLR
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  13. 2024
    Towards LifeSpan Cognitive SystemsYu Wang, Chi Han, Tongtong Wu … Julian McAuleyTrans. Mach. Learn. Res.
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  14. 2024
    Dynamic Graph Convolution Network for Multi-Label Class Incremental LearningYu Wang, Anhui Tan, Shenming GuInternational Conference on Big Data & Artificial Intelli…
  15. 2024
    TCP: Triplet Contrastive-relationship Preserving for Class-Incremental LearningShiyao Li, Xuefei Ning, Shanghang Zhang … Yu WangWACV
  16. 2024
  17. 2024
    Persistence Homology Distillation for Semi-supervised Continual LearningYan Fan, Yu Wang, Pengfei Zhu … Qinghua HuNeurIPS
  18. 2023PDF ↗
  19. 2021
    Few-Shot Continual Learning for Audio ClassificationYu Wang, Nicholas J. Bryan, Mark Cartwright … Justin SalamonICASSP · New York University · Adobe Systems (United States)
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.