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. 2025
    Using Knowledge Replay Strategy to Help Improve the VLM Performance in Embodied RobotsFangyuan Ren, Jiayi Xu, Z. Zheng … Fei ChenIEEE International Conference on Robotics and Biomimetics… · Ningbo University · Ningbo University of Technology · +1
  2. 2025
    Diffuse&Refine: Intrinsic Knowledge Generation and Aggregation for Incremental Object DetectionJianzhou Wang, Yirui Wu, Lixin Yuan … Wenhai WangIJCAI · Hohai University · Ministry of Water Resources of the People's Republic of China · +5
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  3. 2025
    Rethinking softmax in incremental learningZheng Zhai, Jiali Zhang, Haiyu Wang … Qiang SunNeural Networks · Beijing Normal-Hong Kong Baptist University · Beijing Normal University · +4
  4. 2025
    pFedMxF: Personalized Federated Class-incremental Learning with Mixture of Frequency AggregationYifei Zhang, Hao Zhu, Alysa Ziying Tan … Han YuCVPR · Nanyang Technological University · Data Management (Italy) · +2
  5. 2025
    ReFNet: Rehearsal-based graph lifelong learning with multi-resolution framelet graph neural networksMing Li, Xiaoyi Yang, Yuting Chen … Qintai HuInformation Sciences · Zhejiang Normal University · Chinese University of Hong Kong · +1
  6. 2025
    Gradient-Guided Epsilon Constraint Method for Online Continual LearningSong Lai, Changyi Ma, Fei Zhu … Qingfu ZhangNeurIPS · City University of Hong Kong · Chinese University of Hong Kong · +4
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 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.