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.

6 papers of 8,653Sort Recent · Most cited
  1. 2022
    LCFIL: A Loss Compensation Mechanism for Latest Data in Federated Incremental LearningBokai Cao, Weigang Wu, Jieying ZhouIEEE 19th International Conference on Mobile Ad Hoc and S… · Sun Yat-sen University
  2. 2022
    Lifelong Person Re-identification by Pseudo Task Knowledge PreservationWenhang Ge, Junlong Du, Ancong Wu … Wei‐Shi ZhengAAAI · Sun Yat-sen University · Tencent (China)
  3. 2022
    Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear ConnectorGuoliang Lin, Hanlu Chu, Hanjiang LaiCVPR · Sun Yat-sen University · South China Normal University
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  4. 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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  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. 2022
    Discriminative Distillation to Reduce Class Confusion in Continual LearningChanghong Zhong, Zhiying Cui, Wei‐Shi Zheng … Ruixuan WangSpringer LNCS · Sun Yat-sen University · Key Laboratory of Guangdong Province
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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.