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.

57 papers of 6,984 · showing 51–57Sort Recent · Most cited
  1. 2022
    Continual Object Detection via Prototypical Task Correlation Guided Gating MechanismBinbin Yang, Xinchi Deng, Shi Han … Xiaodan LiangCVPR · Sun Yat-sen University · Hong Kong University of Science and Technology · +1
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  2. 2022
    Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled DataYu-Ming Tang, Yi-Xing Peng, Wei‐Shi ZhengCVPR · Ministry of Education of the People's Republic of China · Sun Yat-sen University · +1
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  3. 2023
    Dynamic Support Network for Few-Shot Class Incremental LearningBoyu Yang, Mingbao Lin, Yunxiao Zhang … Qixiang YeTPAMI · University of Chinese Academy of Sciences · Xiamen University · +2
  4. 2023
    Meta-Reinforcement Learning in Non-Stationary and Dynamic EnvironmentsZhenshan Bing, David Lerch, Kai Huang, Alois KnollTPAMI · Technical University of Munich · Sun Yat-sen University · +1
  5. 2021
    Blind Adaptive Gait Planning on Non-stationary Environments via Continual Reinforcement LearningHao Hu, Yang LiuIEEE International Conference on Unmanned Systems (ICUS) · Sun Yat-sen University
  6. 2021
    Deep Metric Learning for Open World Semantic SegmentationJun Cen, Yun Peng, Junhao Cai … Ming LiuICCV · Hong Kong University of Science and Technology · Sun Yat-sen University
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  7. 2020
    Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and MaskingBinzong Geng, Fajie Yuan, Qiancheng Xu … Min YangACL · University of Science and Technology of China · Chinese Academy of Sciences · +7
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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.