Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

9 papers of 11,817Sort Recent · Most cited
  1. 2023
    Create Your World: Lifelong Text-to-Image DiffusionGan Sun, Wen-Qi Liang, Jiahua Dong … Yang CongTPAMI
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  2. 2023
    I3DOD: Towards Incremental 3D Object Detection via PromptingWen-Qi Liang, Gan Sun, Chenxi Liu … Kang-Ru WangIROS
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  3. 2023PDF ↗
  4. 2023
    Heterogeneous Forgetting Compensation for Class-Incremental LearningJiahua Dong, Wenqi Liang, Yang Cong, Gan SunICCV
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  5. 2023
    Gradient-Semantic Compensation for Incremental Semantic SegmentationWei Cong, Yang Cong, Jiahua Dong … Henghui DingIEEE Trans. Multimedia
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  6. 2023
    Self-Paced Weight Consolidation for Continual LearningWei Cong, Yang Cong, Gan Sun … Jiahua DongIEEE TCSVT
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  7. 2023
    Federated Incremental Semantic SegmentationJiahua Dong, Duzhen Zhang, Yang Cong … Dengxin DaiCVPR
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  8. 2023PDF ↗
  9. 2023
    No One Left Behind: Real-World Federated Class-Incremental LearningJiahua Dong, Yang Cong, Gan Sun … Dengxin DaiTPAMI
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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. 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.