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.

4 papers of 6,984Sort Recent · Most cited
  1. 2025
    Rethinking domain-agnostic continual learning via frequency completeness learningJian Peng, Haitao Zhang, Jing Shen … Haifeng LiInformation Fusion · Space Engineering University · University of Chinese Academy of Sciences · +5
  2. 2025
    Pursuing Better Representations: Balancing Discriminability and Transferability for Few-Shot Class-Incremental LearningQi Li, Wei Wang, Hui Fan … Fei WenJournal of Imaging · National University of Defense Technology · Central South University of Forestry and Technology · +2
  3. 2025
    CFSSeg: Closed-Form Solution for Class-Incremental Semantic Segmentation of 2D Images and 3D Point CloudsJia Xu Li, Rui Li, Jianyu Qi … Huiping ZhuangACM International Conference on Multimedia · Central South University · Zhengzhou University · +4
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  4. 2025
    Flexi-FSCIL: Adaptive Knowledge Retention for Breaking the Stability-Plasticity Dilemma in Few-Shot Class-Incremental LearningWufei Xie, Yue Wang, Chenliang Liu … Xue YangICCV · Central South University · Shanghai Jiao Tong University
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 led 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.