Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

5 papers of 6,984Sort Recent · Most cited
  1. 2025
    Prompt-Enhanced: Leveraging language representation for prompt continual learning.Wei Li, D. M. Li, Shitong Shao … Zhen LeiNeural Networks · Southeast University · Duke Kunshan University · +2
  2. 2024
    Class Incremental Learning for Character String RecognitionYijie Hu, Yan‐Ming Zhang, Kaizhu Huang, Qiufeng WangSpringer LNCS · Xi’an Jiaotong-Liverpool University · Chinese Academy of Sciences · +2
  3. 2020
    Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learningFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Amir HussainNeural Networks · Shandong Institute of Automation · Institute of Automation · +7
  4. 2019
    Primitives Generation Policy Learning without Catastrophic Forgetting for Robotic ManipulationFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Amir HussainICDM · Shandong Institute of Automation · University of Chinese Academy of Sciences · +4
  5. 2018
    Guided Policy Search for Sequential Multitask LearningFangzhou Xiong, Biao Sun, Xu Yang … Zhiyong LiuIEEE Transactions · University of Chinese Academy of Sciences · University of Science and Technology Beijing · +4
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.