Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 8,653Sort Recent · Most cited
  1. 2026
    Continual Learning with Clip Text-Prototype and an Orthogonal Pre-Expanded Classification HeadTong Yu, Kanghao Chen, Jiantao Tan … Ruixuan WangICASSP · Sun Yat-sen University · Guangzhou University · +1
  2. 2025
    Dual-modality adaptation in vision-language models for continual learningJiahao Zeng, Wentao Zhang, Kanghao Chen … Ruixuan WangNeural Networks · Sun Yat-sen University · GCI Science & Technology (China) · +1
  3. 2025
    Visual Class Incremental Learning With Textual Priors Guidance Based on an Adapted Vision-Language ModelWentao Zhang, Tong Yu, Ruixuan Wang … Xiaobo YangIEEE Trans. Multimedia · Sun Yat-sen University · Guangzhou University of Chinese Medicine · +1
  4. 2024
    Enhancing Task Identification Through Pseudo-OOD Features for Class-Incremental LearningWeizhuo Zhang, Jiankang Chen, Wentao Zhang … Ruixuan WangSpringer LNCS · Sun Yat-sen University · Key Laboratory of Guangdong Province · +1
  5. 2024
    Continual Learning of Image Classes With Language Guidance From a Vision-Language ModelWentao Zhang, Yujun Huang, Weizhuo Zhang … Ruixuan WangIEEE TCSVT · Sun Yat-sen University · Peng Cheng Laboratory · +1
  6. 2024
    Expand and Merge: Continual Learning with the Guidance of Fixed Text Embedding SpaceYujun Huang, Wentao Zhang, Ruixuan WangIJCNN · Sun Yat-sen University
  7. 2024
    CtF: Mitigating Visual Confusion in Continual Learning Through a Coarse-To-Fine ScreeningZejun Ye, Defeng Zhao, Wentao Zhang, Ruixuan WangSpringer LNCS · Sun Yat-sen University · Key Laboratory of Guangdong Province · +1
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.