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.

6 papers of 11,817Sort Recent · Most cited
  1. 2025
    Continual Learning for VLMs: A Survey and Taxonomy Beyond ForgettingYuyang Liu, Qiuhe Hong, Linlan Huang … Yonghong TianarXiv
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  2. 2024
    Language-Inspired Relation Transfer for Few-Shot Class-Incremental LearningYifan Zhao, Jia Li, Zeyin Song, Yonghong TianTPAMI
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  3. 2024
    CASA: Class-Agnostic Shared Attributes in Vision-Language Models for Efficient Incremental Object DetectionMingyi Guo, Yuyang Liu, Zhi-Yuan Yan … Yonghong TianIEEE International Conference on Multimedia and Expo
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  4. 2024
    Solving the Catastrophic Forgetting Problem in Generalized Category DiscoveryXinzi Cao, Xiawu Zheng, Guanhong Wang … Yonghong TianCVPR
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  5. 2024
    Adaptive Discovering and Merging for Incremental Novel Class DiscoveryGuangyao Chen, Peixi Peng, Yangru Huang … Yonghong TianAAAI
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  6. 2023PDF ↗
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.