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.

10 papers of 11,817Sort Recent · Most cited
  1. 2026
    Evidential Prior Guided Neural Collapse for Open World Object DetectionKewen Xia, Xiaodong Yue, Wei Liu … Yaxin PengIEEE TCSVT
  2. 2026PDF ↗
  3. 2026PDF ↗
  4. 2025
    Re-Fed+: A Better Replay Strategy for Federated Incremental LearningYi-Chen Li, Haozhao Wang, Yi-Ning Qi … Ruixuan LiTPAMI
  5. 2025
    Efficient 4D Gaussian Stream with Low Rank AdaptationZhenhuan Liu, Shuai Liu, Yi-Dong Lu … Wei LiuarXiv
    PDF ↗
  6. 2024
    CD-NGP: A Fast Scalable Continual Representation for Dynamic ScenesZhenhuan Liu, Shuai Liu, Zhi-Wei Ning … Wei LiuarXiv
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  7. 2024
    Developing Incremental Learning Models with PrototypesLi-Chiao Wang, Wei Liu, Chung-Shou LiaoIEEE International Joint Conference on Neural Network
  8. 2024
    A Parameter-efficient Language Extension Framework for Multilingual ASRWei Liu, Jingyong Hou, Dong Yang … Tan LeeInterspeech
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  9. 2024
    ABCF: An Adaptive Balanced Multimodal Website Classification FrameworkZhiyuan Liu, Wei Liu, Xin Tong … Xiaojie WangInternational Conference on Computer Supported Cooperativ…
  10. 2022
    Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA TaskStan Weixian Lei, Difei Gao, Jay Zhangjie Wu … Mike Zheng ShouAAAI
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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.