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. 2023
    IL-NeRF: Incremental Learning for Neural Radiance Fields with Camera Pose AlignmentLetian Zhang, Ming Li, Chen Chen, Jie XuCVPR · Middle Tennessee State University · University of Central Florida · +1
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  2. 2023PDF ↗
  3. 2023
    TARGET: Federated Class-Continual Learning via Exemplar-Free DistillationJie Zhang, Chen Chen, Weiming Zhuang, Lingjuan LyuICCV · ETH Zurich · Sony Corporation (United States)
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  4. 2023
    ConPET: Continual Parameter-Efficient Tuning for Large Language ModelsChenyang Song, Xu Han, Zheni Zeng … Tao YangarXiv
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  5. 2023
    Towards Adversarially Robust Continual LearningTao Bai, Chen Chen, Lingjuan Lyu … Bihan WenICASSP · Nanyang Technological University · Zhejiang University of Science and Technology · +2
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  6. 2023
    Addressing Catastrophic Forgetting in Federated Class-Continual LearningJie Zhang, Chen Chen, Weiming Zhuang, Ling-Juan LvarXiv
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.