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.

8 papers of 11,817Sort Recent · Most cited
  1. 2026
    Class-Anchor-Based Federated Continual Learning for Vehicle Part RecognitionFeng-Yu Huang, Jianwei Guo, Gang Liu, Zhiyu ChenElectronics
  2. 2026
    ORACIL: Conflict-Graph-Based Order-Robust Analytic Class-Incremental LearningGuanjie Wang, Hongyu Sun, Wanjia Li, Yan-Hua DongElectronics
  3. 2026
  4. 2026
  5. 2026
  6. 2026
    Meta-LSTM-Affine: A Memory-Based Meta-Adaptive Affine Modeling Framework for Non-Stationary SystemsYang-Ta Kao, Ching-Ting Tu, Hwei-Jen Lin, Yoshimasa TokuyamaElectronics
  7. 2026
  8. 2026
    Continued Electromagnetic Signal Classification Based on Vector Space SeparationLu Jia, Yan Zhao, Shi-Chuan Chen, Zhi-Jin ZhaoElectronics
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.