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.

7 papers of 6,984Sort Recent · Most cited
  1. 2025
    FM-LoRA: Factorized Low-Rank Meta-Prompting for Continual LearningXiaobing Yu, Jin Yang, Xiao-Ming Wu … Xiaofeng LiuCVPR · Washington University in St. Louis · Yale University
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  2. 2024
    Topology-aware Embedding Memory for Continual Learning on Expanding NetworksXikun Zhang, Dongjin Song, Yixin Chen, Dacheng TaoKDD · The University of Sydney · University of Connecticut · +1
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  3. 2024
    Reconciling shared versus context-specific information in a neural network model of latent causesQihong Lu, Tan T Nguyen, Qiong Zhang … Kenneth A. NormanScientific Reports · Princeton University · Washington University in St. Louis · +3
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  4. 2023
    IOB: integrating optimization transfer and behavior transfer for multi-policy reuseSiyuan Li, Hao Li, Jin Zhang … Chongjie ZhangAutonomous Agents and Multi-Agent Systems · Harbin Institute of Technology · Northwestern Polytechnical University · +2
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  5. 2023
    On-device synaptic memory consolidation using Fowler-Nordheim quantum-tunnelingMustafizur Rahman, Subhankar Bose, Shantanu ChakrabarttyFrontiers · Washington University in St. Louis
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  6. 2023
    Toward a More Neurally Plausible Neural Network Model of Latent Cause InferenceQihong Lu, Tan Tien Nguyen, Uri Hasson … Kenneth A. NormanConference on Cognitive Computational Neuroscience · Princeton University · Washington University in St. Louis · +1
  7. 2019
    Incremental Reinforcement Learning With Prioritized Sweeping for Dynamic EnvironmentsZhi Wang, Chunlin Chen, Han‐Xiong Li … Tzyh‐Jong TarnIEEE/ASME Transactions on Mechatronics · Nanjing University · Central South University · +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 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.