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.

9 papers of 8,653Sort Recent · Most cited
  1. 2022
    Learnware: small models do bigZhihua Zhou, Zhi-Hao TanInformation Sciences · Nanjing University
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  2. 2022
    Online Attentive Kernel-Based Temporal Difference LearningXingguo Chen, Guang Yang, Shangdong Yang … Yang GaoKnowledge-Based Systems · Beijing Technology and Business University · Nanjing University of Posts and Telecommunications · +3
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  3. 2022
    Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement LearningJinmei Liu, Zhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  4. 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
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  5. 2022
    Few-Shot Class-Incremental Learning by Sampling Multi-Phase TasksDa-Wei Zhou, Han-Jia Ye, Liang Ma … De-Chuan ZhanTPAMI · Nanjing University
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  6. 2022
    Forward Compatible Few-Shot Class-Incremental LearningDa-Wei Zhou, Fuyun Wang, Han-Jia Ye … De‐Chuan ZhanCVPR · Nanjing University
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  7. 2022
    A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement LearningZhi Wang, Chunlin Chen, Daoyi DongIEEE Trans. Cybernetics · Nanjing University · University of Canberra · +1
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  8. 2022
    Unified Question Generation with Continual Lifelong LearningWei Yuan, Hongzhi Yin, Tieke He … Lizhen CuiACM Web Conference 2022 · The University of Queensland · Nanjing University · +2
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  9. 2022
    Adaptive Feature Generation for Online Continual Learning from Imbalanced DataYingchun Jian, Jinfeng Yi, Lijun ZhangSpringer LNCS · Nanjing University · Jingdong (China)
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.