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.

9 papers of 6,984Sort Recent · Most cited
  1. 2020
    IExpressNet: Facial Expression Recognition with Incremental ClassesJunjie Zhu, Bingjun Luo, Sicheng Zhao … Yue GaoACM International Conference on Multimedia · Tsinghua University · University of California, Berkeley · +1
  2. 2020
    Measuring Information Transfer in Neural NetworksXiao Zhang, Xingjian Li, Dejing Dou, Ji WuarXiv · Tsinghua University · Baidu (China)
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  3. 2020
    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu … Ding ZhaoNeurIPS · Carnegie Mellon University · Tsinghua University · +1
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  4. 2020
    Maintaining Discrimination and Fairness in Class Incremental LearningBowen Zhao, Xi Xiao, Guojun Gan … Shu‐Tao XiaCVPR · Peng Cheng Laboratory · Tsinghua University
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  5. 2020
    OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep LearningQi She, Fan Feng, Xinyue Hao … Rosa H. M. ChanICRA · City University of Hong Kong · Tsinghua University · +4
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  6. 2020
    Multimodal Continual Learning Using Online Dictionary UpdatingFuchun Sun, Huaping Liu, Chao Yang, Bin FangIEEE TCDS · Foshan University · Tsinghua University
  7. 2020
    Continual Relation Learning via Episodic Memory Activation and ReconsolidationXu Han, Yi Dai, Tianyu Gao … Jie ZhouACL · Intelligent Systems Research (United States) · Intelligent Health (United Kingdom) · +3
  8. 2020
    Continual Learning for Natural Language Generation in Task-oriented Dialog SystemsFei Mi, Liangwei Chen, Mengjie Zhao … Boi FaltingsEMNLP · École Polytechnique Fédérale de Lausanne · LMU Klinikum · +2
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  9. 2020
    Generative Memory for Lifelong LearningXin Su, Shangqi Guo, Tian Tan, Feng ChenTNNLS · Beijing Advanced Sciences and Innovation Center · Tsinghua University · +1
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.