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.

5 papers of 6,984Sort Recent · Most cited
  1. 2025
    Clo-HDnn: A 4.66 TLOPS/W and 3.78 TOPS/W Continual On-Device Learning Accelerator with Energy-Efficient Hyperdimensional Computing via Progressive SearchChang Eun Song, Weihong Xu, Keming Fan … Mingu KangSymposium on VLSI Technology and Circuits (VLSI Technolog… · University of California San Diego · Taiwan Semiconductor Manufacturing Company (Taiwan)
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  2. 2024
    Intelligence Beyond the Edge using Hyperdimensional ComputingXiaofan Yu, Anthony Thomas, Ivannia Gomez Moreno … Tajana RosingACM/IEEE International Conference on Information Processi… · University of California San Diego · CETYS Universidad
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  3. 2024
    Evolve: Enhancing Unsupervised Continual Learning with Multiple ExpertsXiaofan Yu, Tajana Rosing, Yunhui GuoWACV · University of California San Diego
  4. 2023
    SCALE: Online Self-Supervised Lifelong Learning without Prior KnowledgeXiaofan Yu, Yunhui Guo, Sicun Gao, Tajana RosingCVPR · University of California San Diego
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  5. 2019
    Learning with Long-term Remembering: Following the Lead of Mixed Stochastic GradientYunhui Guo, Mingrui Liu, Tianbao Yang, Tajana RosingarXiv · University of California San Diego · University of Iowa
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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 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.