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.

9 papers of 8,653Sort Recent · Most cited
  1. 2026
    Adaptive Continual Learning for Online Visual Object Tracking via Dynamic Grassmannian Appearance ModelingJinglin Zhou, Tianyang Xu, Xuefeng Zhu … Josef KittlerIEEE TCSVT · Jiangnan University · University of Surrey
  2. 2025
    Serial Over Parallel: Learning Continual Unification for Multi-Modal Visual Object Tracking and BenchmarkingZhangyong Tang, Tianyang Xu, Xuefeng Zhu … Josef KittlerACM International Conference on Multimedia · Jiangnan University · Nanjing University of Science and Technology · +1
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  3. 2025
    PSMP: Category Prototype-Guided Streaming Multi-Level Perturbation for Online Open-World Object DetectionShibo Gu, Meng Sun, Zhihao Zhang … Ziliang ChenSymmetry · Qingdao Academy of Intelligent Industries · Institute of Software · +3
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  4. 2025
    Similarity-based prototype reconstruction and feature reorganization for non-exemplar class incremental learningChao Zhou, Jun Sun, Vasile Palade, Xiao‐Jun WuNeural Networks · Jiangnan University · Coventry University
  5. 2025
    Fed-OGD: Mitigating Straggler Effects in Federated Learning via Orthogonal Gradient DescentWei Li, Zicheng Shen, Xiulong Liu … Jiaxing ShenIEEE Transactions · Jiangnan University · Tianjin University · +1
  6. 2025
    Knowledge-guided prompt-based continual learning: Aligning task-prompts through contrastive hard negativesHengyang Lu, Lauren Lin, Chenyou Fan … Xiao‐Jun WuKnowledge-Based Systems · Jiangnan University · South China Normal University
  7. 2024
  8. 2024
    FRMM: Feature Reprojection for Exemplar-Free Class-Incremental LearningHao Wang, Jing ChenSpringer LNCS · Jiangnan University
  9. 2023
    A novel data-free continual learning method with contrastive reversionChuhan Wu, Runshan Xie, Shitong WangInternational Journal of Machine Learning and Cybernetics · Jiangnan University
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.