Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

3 papers of 7,070Sort Recent · Most cited
  1. 2026
    Quadruplet Augmentation With Attribute and Structure Invariance for Online Continual LearningJiamin Wu, Shaofan Wang, Yanan Sun … Baocai YinMemberTPAMI · Beijing University of Technology · Beijing Academy of Artificial Intelligence
  2. 2026
    Functionality Separation: Rethinking Dual-Stream Networks for Class-Incremental LearningQi Gao, Xiaoyan Li, Zhongfan Sun … Wen GaoIEEE TCSVT · Beijing University of Technology · Imperial College London · +1
  3. 2025
    Dual-Attention Transformers for Class-Incremental Learning: A Tale of Two MemoriesShaofan Wang, Weixing Wang, Yanfeng Sun … Baocai YinIEEE Trans. Multimedia · Beijing University of Technology · The University of Sydney
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.