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.

5 papers of 8,653Sort Recent · Most cited
  1. 2023
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS · Shanghai Zhangjiang Laboratory · Tsinghua University · +5
  2. 2023
    Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic SegmentationYuwei Yang, Munawar Hayat, Jin Zhao … Yinjie LeiCVPR · Sichuan University · Australian Regenerative Medicine Institute · +1
  3. 2021
    Overcome Anterograde Forgetting with Cycled Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiarXiv
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  4. 2021
    Reviewing continual learning from the perspective of human-level intelligenceYifan Chang, Wenbo Li, Jian Peng … Haifeng LiarXiv
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  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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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.