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.

14 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
    An active unlearning framework for continual learningXuemei Cao, Yong-Hao Li, Xiangkun Wang … Xin YangScientia Sinica Informationis
  3. 2025PDF ↗
  4. 2025
    Ten Challenging Problems in Federated Foundation ModelsTao Fan, Hanlin Gu, Xuemei Cao … Qiang YangTKDE
    PDF ↗
  5. 2024PDF ↗
  6. 2024
  7. 2024PDF ↗
  8. 2024PDF ↗
  9. 2024
    Toward a Dynamic Future With Adaptable Computing and Network Convergence (ACNC)Masoud Shokrnezhad, Hao Yu, T. Taleb … Cédric WestphalIEEE Network
    PDF ↗
  10. 2024
  11. 2023
    Federated Continual Learning via Knowledge Fusion: A SurveyXin Yang, Hao Yu, Xin Gao … Tianrui LiTKDE
    PDF ↗
  12. 2023
  13. 2019
    An End-to-End Architecture for Class-Incremental Object Detection with Knowledge DistillationHao Yu, Yanwei Fu, Yu–Gang Jiang, Qi TianIEEE International Conference on Multimedia and Expo (ICME) · Fudan University · Jilian Technology Group (China) · +1
  14. 2019
    Take Goods from Shelves: A Dataset for Class-Incremental Object DetectionHao Yu, Yanwei Fu, Yu–Gang Jiang2019 on International Conference on Multimedia Retrieval · Fudan University · Jilian Technology Group (China)
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.