Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 4,574Sort Recent · Most cited
  1. 2024
    MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality AssessmentKanglei Zhou, Liyuan Wang, Xingxing Zhang … Xiaohui LiangECCV · Durham University · Beihang University · +2
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  2. 2024
    Prompting Continual Person SearchPengcheng Zhang, Xiaohan Yu, Bai Xiao … Xin NingACM International Conference on Multimedia · Beihang University · Macquarie University · +2
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  3. 2024
    NC2D: Novel Class Discovery for Node ClassificationYue Hou, X. R. Chen, He Zhu … Ke XuCIKM · Beihang University · Communication University of China
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  4. 2024
    SCARF: Scalable Continual Learning Framework for Memory‐efficient Multiple Neural Radiance FieldsYuze Wang, Junyi Wang, Chen Wang … Yue QiComputer Graphics Forum · Beihang University · Shandong University of Science and Technology · +3
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  5. 2024PDF ↗
  6. 2024
    Hessian Aware Low-Rank Perturbation for Order-Robust Continual LearningJiaqi Li, Yuanhao Lai, Rui Wang … Fan ZhouTKDE · Western University · Vector Institute · +3
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  7. 2024PDF ↗
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times, and only papers with a PDF we can point you at, so every title opens the paper itself. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.