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. 2026PDF ↗
  2. 2026
    Hierarchical Dual-Subspace Decoupling for Continual Learning in Vision-Language ModelsMengxin Qin, Xiang Zhang, Kun-Juan Wei … Cheng DengarXiv
    PDF ↗
  3. 2026PDF ↗
  4. 2026PDF ↗
  5. 2025
    Class Incremental Learning via Contrastive Complementary AugmentationXi Wang, Xu Yang, Kun-Juan Wei … Cheng DengTIP
  6. 2025
  7. 2025
    Dynamic Adapter Tuning for Long-Tailed Class-Incremental LearningYanan Gu, Muli Yang, Xu Yang … Cheng DengWACV
  8. 2025
    Memory-Enhanced Confidence Calibration for Class-Incremental Unsupervised Domain AdaptationJia-Ping Yu, Muli Yang, Aming Wu, Cheng DengIEEE Trans. Multimedia
  9. 2025
  10. 2024
    Navigating Continual Test-time Adaptation with Symbiosis KnowledgeXu Yang, Moqi Li, Jie Yin … Cheng DengIJCAI
  11. 2024
  12. 2024
  13. 2024
  14. 2022
    Incremental Embedding Learning With Disentangled Representation TranslationKun Wei, Da Chen, Yuhong Li … Dacheng TaoTNNLS · Xidian University · Alibaba Group (China) · +1
  15. 2022
  16. 2021
    Incremental Zero-Shot LearningKun Wei, Cheng Deng, Xu Yang, Dacheng TaoIEEE Trans. Cybernetics · Xidian University · Jingdong (China)
  17. 2021
    Class-Incremental Instance Segmentation via Multi-Teacher NetworksYanan Gu, Cheng Deng, Kun WeiAAAI · Xidian University
  18. 2020
    Incremental Embedding Learning via Zero-Shot TranslationKun Wei, Cheng Deng, Xu Yang, Maosen LiAAAI · Xidian University
    PDF ↗
  19. 2020
    Lifelong Zero-Shot LearningKun Wei, Cheng Deng, Xu YangIJCAI · Xidian University
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.