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. 2025
    Task-Aware Multi-Expert Architectures for Lifelong Deep LearningJianyu Wang, Jacob Nean-Hua Sheikh, Cat P. Le, Hoda BidkhoriWinter Simulation Conference (WSC) · George Mason University · Duke University
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  2. 2025
    Knowledge-guided Continual Learning for Behavioral Analytics SystemsYasas Senarath, Hemant PurohitIEEE 7th International Conference on Cognitive Machine In… · George Mason University
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  3. 2021
    Schematic Memory Persistence and Transience for Efficient and Robust Continual LearningYuyang Gao, Giorgio A. Ascoli, Liang ZhaoNeural Networks · Emory University · George Mason University · +2
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  4. 2021
    Federated Continuous Learning With Broad Network ArchitectureJunqing Le, Xinyu Lei, Nankun Mu … Xiaofeng LiaoIEEE Trans. Cybernetics · Southwest University · Michigan State University · +2
  5. 2019
    Task-adaptive incremental learning for intelligent edge devicesZhuwei Qin, Fuxun Yu, Xiang ChenACM/IEEE Symposium on Edge Computing · George Mason University
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  6. 2002
    Incremental learning with partial instance memoryMarcus A. Maloof, Ryszard S. MichalskiArtificial Intelligence · Georgetown University · George Mason University · +1
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.