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.

17 papers of 8,653Sort Recent · Most cited
  1. 2026
    Continual Learning in TransitionZhiyan Hou, Dan Zhang, Tao Feng … Tat-Seng ChuaarXiv
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  2. 2026
    GUI-AC: Enhancing Continual Learning in GUI AgentsCan Lin, Tao Feng, Hangjie Yuan … Zhonghong OuarXiv
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  3. 2026
    A Faster Path to Continual LearningWei Li, Hangjie Yuan, Zixiang Zhao … Tao FengCVPR
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  4. 2026
    Continual GUI AgentsZiwei Liu, Borui Kang, Hangjie Yuan … Tao FengarXiv
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  5. 2025
    Dynamic Multi-Layer Null Space Projection for Vision-Language Continual LearningBorui Kang, Lei Wang, Zhiping Wu … Weiwei LiICCV · Nanjing University · University of Wollongong · +2
  6. 2025PDF ↗
  7. 2026PDF ↗
  8. 2025PDF ↗
  9. 2026
    Adapt before Continual LearningAlex Lu, Tao Feng, Holly Yuan … Yanan SunAAAI
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  10. 2025PDF ↗
  11. 2024
    UniGrad-FS: Unified Gradient Projection With Flatter Sharpness for Continual LearningWei Li, Tao Feng, Hangjie Yuan … Ziwei LiuIEEE TII · Sichuan University · Chengdu University · +3
  12. 2024
    Revisiting class-incremental object detection: An efficient approach via intrinsic characteristics alignment and task decouplingLiang Bai, Hong Song, Tao Feng … Jian YangExpert Systems with Applications · Beijing Institute of Technology · Tsinghua University
  13. 2024
    Make Continual Learning Stronger via C-FlatAng Bian, Wei Li, Hangjie Yuan … Tao FengNeurIPS
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  14. 2023
    Refined Response Distillation for Class-Incremental Player DetectionLiang Bai, Hangjie Yuan, Tao Feng … Jian YangarXiv
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  15. 2022
    Progressive Learning without ForgettingTao Feng, Hangjie Yuan, Mang Wang … Jianzhou ZhangarXiv
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  16. 2022
    Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response DistillationTao Feng, Mang Wang, Hangjie YuanCVPR · Alibaba Group (United States) · Zhejiang University
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  17. 2021PDF ↗
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.