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
  2. 2026
    Knowledge-Augmented Continual Learning System for Drilling Efficiency Optimization in Complex FormationsRui Zhang, Qihao Li, Xianzhi Song … Chaochen WangChinese Control and Decision Conference
  3. 2026
    Training-Efficient Knee Joint Moment Estimation During Stair Ascent and Descent via a Broad Learning SystemGuoyu Zuo, Minghui Zhang, Qifei Wu, Shuangyue YuChinese Control and Decision Conference
  4. 2026
    UIKG: New Uncertain-Dynamic Incremental Knowledge GraphsZhang-Cong Xu, Gumin Jin, Guangyao Wang, Jian-Xun LiChinese Control and Decision Conference
  5. 2025
  6. 2025
    Memory-Free Incremental Learning on Pretrained Diffusion ModelHao-hao Zhang, Jian-Wei LiuChinese Control and Decision Conference
  7. 2025
    Text-to-Image Diffusion Models via Additive Attention-Based Image Fusion PromptsG. Diao, Jian-Wei LiuChinese Control and Decision Conference
  8. 2025
    A Feedback-Driven Learning Framework for Adaptive Neural Motion PlannerHuaihang Zheng, Shangfei Liu, Junzheng WangChinese Control and Decision Conference
  9. 2024
  10. 2024
    Incremental Learning Method for Robot Error Based on GWO-XGBoost AlgorithmZi-Wei Lu, Zhaoyang Liao, Jin-Zhu Wu … Zhi-Hao XuChinese Control and Decision Conference
  11. 2024
    A Log Anomaly Detection Based on Incremental Contrastive LearningYing TianChinese Control and Decision Conference
  12. 2024
    Few-Shot Class Incremental Learning for Packaging Defects with Double Class Feature InteractionLi-Ming Zhu, Bo Zhang, Dan Zhao, Hongtao HuChinese Control and Decision Conference
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.