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.

16 papers of 11,817Sort Recent · Most cited
  1. 2025
    LiteUpdate: A Lightweight Framework for Updating AI-Generated Image DetectorsJiajie Lu, Zhenkan Fu, Na Zhao … Neng H. YuIEEE TCSVT
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  2. 2025
    Few-Shot Class-Incremental Learning via Asymmetric Supervised Contrastive LearningDuo Liu, Linglan Zhao, Zhongqiang Zhang … Liang WangIEEE TCSVT
  3. 2025
    Mamba Adapter: Efficient Multi-Modal Fusion for Vision-Language TrackingLiang-Tao Shi, Bineng Zhong, Qi-Hua Liang … Shuxiang SongIEEE TCSVT
  4. 2025
    Class-Aware Prompting for Federated Few-Shot Class-Incremental LearningFang liang, Yu-Wei Zhan, Jiale Liu … Xin-Shun XuIEEE TCSVT
  5. 2025
  6. 2025PDF ↗
  7. 2025
  8. 2025
    Joint Memory Optimization for Continual LearningZhiheng Ma, Yaohui Ma, Xiaopeng Hong … Shizhou ZhangIEEE TCSVT
  9. 2025
  10. 2025
    Prompt-Based Concept Learning for Few-Shot Class-Incremental LearningShuo Li, Fang Liu, Licheng Jiao … Wenping MaIEEE TCSVT
  11. 2025
    Learn by Reasoning: Analogical Weight Generation for Few-Shot Class-Incremental LearningJizhou Han, Chenhao Ding, Yuhang He … Yihong GongIEEE TCSVT
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  12. 2025
    Class Incremental Learning With Less Forgetting Direction and Equilibrium PointHaitao Wen, Heqian Qiu, Lanxiao Wang … Hongliang LiIEEE TCSVT
  13. 2025PDF ↗
  14. 2025
    Boosting Deepfake Detection Generalizability via Expansive Learning and Confidence JudgementKuiyuan Zhang, Zeming Hou, Zhong-Yun Hua … Leo Yu ZhangIEEE TCSVT
  15. 2025
  16. 2025
    Reformulating Classification as Image-Class Matching for Class Incremental LearningYu-Song Hu, Zichen Liang, Xialei Liu … Ming-Ming ChengIEEE TCSVT
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.