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.

5 papers of 8,653Sort Recent · Most cited
  1. 2022
    ISM-Net: Mining incremental semantics for class incremental learningZihuan Qiu, Linfeng Xu, Zhichuan Wang … Hongliang LiNeurocomputing · University of Electronic Science and Technology of China
  2. 2022
    Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class RepresentationGuangchen Shi, Yirui Wu, Jun Liu … Tong LüACM International Conference on Multimedia · Hohai University · Singapore University of Technology and Design · +3
    PDF ↗
  3. 2022
    Class Gradient Projection For Continual LearningCheng Chen, Ji Zhang, Jingkuan Song, Lianli GaoACM International Conference on Multimedia · University of Electronic Science and Technology of China · Peng Cheng Laboratory
    PDF ↗
  4. 2022
    Feature Distribution Distillation-Based Few Shot Class Incremental LearningJuntao Zhu, Guangle Yao, Wenlong Zhou … Wei ZhangICPR · Chengdu University of Technology · Yibin University · +4
  5. 2022
    Continual Referring Expression Comprehension via Dual Modular MemorizationHeng Tao Shen, Cheng Chen, Peng Wang … Jingkuan SongTIP · University of Electronic Science and Technology of China · Peng Cheng Laboratory · +2
    PDF ↗
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.