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.

12 papers of 11,817Sort Recent · Most cited
  1. 2025
    Catastrophic Forgetting Mitigation via Discrepancy-Weighted Experience ReplayXinrun Xu, Jianwen Yang, Qiuhong Zhang … Shan JiangICANN
    PDF ↗
  2. 2025
    Brain Generative Replay for Continual LearningJian-Guo Zhou, Dong-Jun Liu, Wanzeng KongICANN
  3. 2025
  4. 2024PDF ↗
  5. 2024
    An Energy Sampling Replay-Based Continual Learning FrameworkXingzhong Zhang, Joon Huang Chuah, C. Loo, Stefan WermterICANN
  6. 2023PDF ↗
  7. 2023
    Dynamic Memory-Based Continual Learning with Generating and ScreeningSiying Tao, Jinyang Huang, Xiang Zhang … Yu GuICANN
  8. 2022
    Adaptive Online Domain Incremental Continual LearningN. Gunasekara, Heitor Murilo Gomes, A. Bifet, Bernhard PfahringerICANN
  9. 2022
  10. 2022
  11. 2019
    Transfer Learning with Sparse Associative MemoriesQuentin Jodelet, Vincent Gripon, M. HagiwaraICANN
    PDF ↗
  12. 1994
    Catastrophic Interference in Learning Processes by Neural NetworksEliano Pessa, Maria Pietronilla PennaICANN · Sapienza University of Rome
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.