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. 2024
    Solving the Catastrophic Forgetting Problem in Generalized Category DiscoveryXinzi Cao, Xiawu Zheng, Guanhong Wang … Yonghong TianCVPR · Sun Yat-sen University · Peng Cheng Laboratory · +2
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  2. 2023
    Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental LearningZeyin Song, Yifan Zhao, Yujun Shi … Yonghong TianCVPR · Peking University · National University of Singapore · +1
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  3. 2023
    VQACL: A Novel Visual Question Answering Continual Learning SettingXi Zhang, Feifei Zhang, Changsheng XuCVPR · Chinese Academy of Sciences · University of Chinese Academy of Sciences · +2
  4. 2023
    Regularizing Second-Order Influences for Continual LearningZhicheng Sun, Yadong Mu, Gang HuaCVPR · Peking University · Peng Cheng Laboratory
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  5. 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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  6. 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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  7. 2020
    Few-Shot Class-Incremental LearningXiaoyu Tao, Xiaopeng Hong, Xinyuan Chang … Yihong GongCVPR · Xi'an Jiaotong University · Peng Cheng Laboratory
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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. 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.