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.

60 papers of 8,653 · showing 51–60Sort Recent · Most cited
  1. 2022
    Adaptive Progressive Continual LearningJu Xu, Jin Ma, Xuesong Gao, Zhanxing ZhuTPAMI · Peking University · Shandong University · +4
  2. 2021
    Continual Learning by Using Information of Each Class HolisticallyWenpeng Hu, Qi Qin, Mengyu Wang … Bing LiuAAAI · Peking University
  3. 2021
    Continual Learning for Neural Machine TranslationYue Cao, Haoran Wei, Boxing Chen, Xiaojun WanNAACL · Peking University · Alibaba Group (United States)
  4. 2021
    Principal Gradient Direction and Confidence Reservoir Sampling for Continual LearningZhiyi Chen, Tong LinSpringer LNCS · Georgia Institute of Technology · Peking University · +1
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  5. 2020
    IROS 2019 Lifelong Robotic Vision: Object Recognition Challenge [Competitions]Heechul Bae, Eoin Brophy, Rosa H. M. Chan … Liguang ZhouIEEE Robotics & Automation Magazine · Electronics and Telecommunications Research Institute · Dublin City University · +9
  6. 2020
    Disentangle-based Continual Graph Representation LearningXiaoyu Kou, Yankai Lin, Shaobo Liu … Yan ZhangEMNLP · Peking University · Tencent (China)
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  7. 2020
    Using the Past Knowledge to Improve Sentiment ClassificationQi Qin, Wenpeng Hu, Bing LiuEMNLP · Peking University · King University
  8. 2019
    Bayesian Optimized Continual Learning with Attention MechanismJu Xu, Jin Ma, Zhanxing ZhuarXiv · Peking University
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  9. 2018
    Life-long Cross-media Correlation LearningJinwei Qi, Yuxin Peng, Yunkan ZhuoACM international conference on Multimedia · Peking University
  10. 2014
    Error-Driven Incremental Learning in Deep Convolutional Neural Network for Large-Scale Image ClassificationTianjun Xiao, Jiaxing Zhang, Kuiyuan Yang … Zheng ZhangACM international conference on Multimedia · Peking University · Microsoft Research Asia (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. 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.