Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 8,653Sort Recent · Most cited
  1. 2026
    Rethinking domain-agnostic continual learning via frequency completeness learningJian Peng, Haitao Zhang, Jing Shen … Haifeng LiInformation Fusion · Space Engineering University · University of Chinese Academy of Sciences · +5
  2. 2023
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS · Shanghai Zhangjiang Laboratory · Tsinghua University · +5
  3. 2021
    Learning by Active Forgetting for Neural NetworksJian Peng, Xian Sun, Min Deng … Haifeng LiarXiv · Central South University
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  4. 2022
    MFS: A Brain-Inspired Memory Formation System for GANYifan Chang, Yifan Wang, Jian Peng … Wenbo LiIEEE Transactions · University of Science and Technology of China · Anhui University · +3
  5. 2019
    Overcoming Long-Term Catastrophic Forgetting Through Adversarial Neural Pruning and Synaptic ConsolidationJian Peng, Bo Tang, Hao Jiang … Haifeng LiTNNLS · Central South University · Mississippi State University · +3
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  6. 2020
    Memory Protection Generative Adversarial Network (MPGAN): A Framework to Overcome the Forgetting of GANs Using Parameter Regularization MethodsYifan Chang, Wenbo Li, Jian Peng … Yingliang HuangIEEE Access · University of Science and Technology of China · Hefei Institute of Technology Innovation · +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.