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.

7 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
    Decision Boundary Drift: A Security, Privacy, and Trust Risk of Continual Learning for Agentic AI in Edge NetworksKaixiang Yang, Yue-Bin Xu, Zhi-Hao Li … C. L. Philip ChenIEEE Transactions
  3. 2025
    Hybrid Ensemble Framework for Imbalanced Data Streams With Concept DriftMianfen Lin, Zhiwen Yu, Kaixiang Yang, C. L. Philip ChenIEEE Transactions
  4. 2025
  5. 2024
    Detecting Cloud Anomaly via Broad Network-Based Contrastive AutoencoderGuo-Xiang Zhong, Fagui Liu, Jun Jiang … C. L. Philip ChenIEEE Transactions
  6. 2023
    Broad Minimax Probability Learning System and its Application in Regression ModelingFei Chu, Tao Liang, C. L. Philip Chen … Xuesong WangIEEE Transactions
  7. 2020
    Neural-Learning-Based Force Sensorless Admittance Control for Robots With Input DeadzoneGuangzhu Peng, C. L. Philip Chen, Wei He, Chenguang YangIEEE Transactions · University of Macau · South China University of Technology · +3
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.