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.

4 papers of 8,653Sort Recent · Most cited
  1. 2024
    Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution DetectionZhou, Zhiping, Xuchen Xie, Yiqiao Qiu … Ruixuan WangNeurocomputing
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  2. 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
  3. 2024
    Expand and Merge: Continual Learning with the Guidance of Fixed Text Embedding SpaceYujun Huang, Wentao Zhang, Ruixuan WangIJCNN · Sun Yat-sen University
  4. 2024
    Generalizable Two-Branch Framework for Image Class-Incremental LearningChao Wu, Xiaobin Chang, Ruixuan WangICASSP · Sun Yat-sen University
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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. By default it shows the 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. The rest are one click away under “All papers”. 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.