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. 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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  2. 2025
    CSTA: Spatial-Temporal Causal Adaptive Learning for Exemplar-Free Video Class-Incremental LearningTieyuan Chen, Huabin Liu, Chern Hong Lim … Weiyao LinIEEE TCSVT · Shanghai Jiao Tong University · Monash University Malaysia · +4
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  3. 2025
    Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot ManipulationY. Lawrence Yao, Siao Liu, Haoming Song … Dong WangCVPR · ShangHai JiAi Genetics & IVF Institute · Shanghai Artificial Intelligence Laboratory · +2
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  4. 2025
    Imbalance Mitigation for Continual Learning via Knowledge Decoupling and Dual Enhanced Contrastive LearningZhong Ji, Zhanyu Jiao, Qiang Wang … Jungong HanTNNLS · Tianjin University · Beijing Academy of Artificial Intelligence · +2
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.