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. 2023
    Rethinking Few-Shot Class-Incremental Learning With Open-Set Hypothesis in Hyperbolic GeometryYawen Cui, Zitong Yu, Wei Peng … Li LiuIEEE Trans. Multimedia · University of Oulu · Great Bay University · +3
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  2. 2023
    Slow-Fast Time Parameter Aggregation Network for Class-Incremental Lip ReadingXueyi Zhang, Chengwei Zhang, Tao Wang … Haizhou LiACM International Conference on Multimedia · National University of Defense Technology · Shenzhen Research Institute of Big Data · +3
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  3. 2023
    Adaptive Self-Supervised Continual LearningLilei Wu, Zhen Wang, Jie LiuFrontiers · National University of Defense Technology · Tsinghua University
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  4. 2023
    Incremental Learning for Simultaneous Augmentation of Feature and ClassChenping Hou, Shilin Gu, Chao Xu, Yuhua QianTPAMI · National University of Defense Technology · Shanxi University
  5. 2023
    CCL: Continual Contrastive Learning for LiDAR Place RecognitionJiafeng Cui, Xieyuanli ChenRA-L · National University of Defense Technology
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  6. 2023
    Decoupled Two-Phase Framework for Class-Incremental Few-Shot Named Entity RecognitionYifan Chen, Zhen Huang, Minghao Hu … Xicheng LuTsinghua Science & Technology · National University of Defense Technology · PLA Academy of Military Science
  7. 2023
    Multi-granularity knowledge distillation and prototype consistency regularization for class-incremental learningYanyan Shi, Dianxi Shi, Dianxi Shi … Chunping QiuNeural Networks · National University of Defense Technology · National Defense 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. 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.