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.

17 papers of 11,817Sort Recent · Most cited
  1. 2026
    EvoHarnessBench: Can Your Agents Keep Pace with an Evolving Harness?Zi-Xuan Ke, Vaidehi Patil, Hai-Zhou Shi … Shafiq JotyarXiv
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  2. 2026PDF ↗
  3. 2026
    Guided Prompt Evolution for Vision-Language Models AdaptationE. Zhang, Jia-Yun Li, Yanlong Wang … Yang LiarXiv
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  4. 2025PDF ↗
  5. 2025
    Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligenceXiang He, Dongcheng Zhao, Yang Li … Yi ZengScience Advances
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  6. 2025PDF ↗
  7. 2025
  8. 2024
    Similarity-based context aware continual learning for spiking neural networksBing Han, Feifei Zhao, Yang Li … Yi ZengNeural Networks
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  9. 2024
  10. 2024
    Self-Evolution Policy Learning: Leveraging Basic Tasks to Complex OnesQi-Zheng Chen, Wen-Wen Xiao, Yang Li, Xiang-Feng LuoInternational Seminar on Artificial Intelligence, Network…
  11. 2024PDF ↗
  12. 2023PDF ↗
  13. 2022PDF ↗
  14. 2022
    XST: A Crossbar Column-wise Sparse Training for Efficient Continual LearningFan Zhang, Yang Li, Jian Meng … Deliang FanDesign, Automation & Test in Europe Conference &… · Arizona State University
  15. 2022
    XBM: A Crossbar Column-wise Binary Mask Learning Method for Efficient Multiple Task AdaptionFan Zhang, Yang Li, Jian Meng … Deliang FanAsia and South Pacific Design Automation Conference (ASP-… · Arizona State University
  16. 2020
    SEM: Adaptive Staged Experience Access Mechanism for Reinforcement LearningJianshu Wang, Xinzhi Wang, Xiangfeng Luo … Yang LiIEEE 32nd International Conference on Tools with Artifici… · Shanghai University of Engineering Science
  17. 2020
    Learn#: A Novel incremental learning method for text classificationGuangxu Shan, Shiyao Xu, Yang Li … Yang XiangExpert Systems with Applications · Tongji University
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.