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.

12 papers of 11,817Sort Recent · Most cited
  1. 2026
    Alleviating Regional Shortcuts for Few-Shot Class-Incremental LearningHaichen Zhou, Y. Lyu, Yixiong Zou … Yu-Hua LiIEEE Trans. Multimedia
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  2. 2026PDF ↗
  3. 2026
    Generalizable and Adaptive Continual Learning Framework for AI-Generated Image DetectionHan-Yi Wang, Jun Lan, Yaoyu Kang … Shilin WangIEEE Trans. Multimedia
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  4. 2026
    Distortion-Sensitive Masked Autoencoder for Omnidirectional Video Quality AssessmentZongyao Hu, Lixiong Liu, Ke Gu … A. BovikIEEE Trans. Multimedia
  5. 2026
    PIC-CMH: Efficient Prompt-Infused Continual Cross-Modal HashingFengling Li, Wenhao Liu, Tianshi Wang … Xiaojun ChangIEEE Trans. Multimedia
  6. 2026
    Toward Bidirectional Adaptability for Few-Shot Class-Incremental Learning With Forward-Backward Knowledge TransferBingzhi Chen, Zhiming Chen, Sudong Cai … Sheng-Li XieIEEE Trans. Multimedia
  7. 2026
    Continual Learning Via Gradient-Regularized Based Dynamic Expansion ModelFei Ye, Yong Zhong, Qi-He Liu … Shi-Jie ZhouIEEE Trans. Multimedia
  8. 2026
    DCFD-FFCL:Decoupling Causal Effects and Feature Drift for Freedom-Forgetting Continual LearningJing Yang, Qinglang Li, Xinyu Zhou … M. NegnevitskyIEEE Trans. Multimedia
  9. 2026
    Debiased Hypernetworks Are Generative Class-Incremental LearnersShaofan Wang, Pengli Guo, Weixing Wang … Baocai YinIEEE Trans. Multimedia
  10. 2026
  11. 2026
    Topology-Evolving Semantic Adaptation for Few-Shot Class-Incremental Action RecognitionXingyu Zhu, Binqian Xu, Jia-Chao Zhang … Xiangbo ShuIEEE Trans. Multimedia
  12. 2026
    Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning PerspectiveLeyuan Wang, Liuyu Xiang, Yunlong Wang … Zhaofeng HeIEEE Trans. Multimedia
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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.