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.

9 papers of 8,653Sort Recent · Most cited
  1. 2026
    Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future DirectionsSarthak Kumar Maharana, Shambhavi Mishra, Yunbei Zhang … Yunhui GuoTMLR
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  2. 2026
    Modality-Inconsistent Continual Learning of Multimodal Large Language ModelsWeiguo Pian, Shijian Deng, Shentong Mo … Yapeng TianTMLR
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  3. 2024
    Continual Audio-Visual Sound SeparationWeiguo Pian, Yiyang Nan, Shijian Deng … Yapeng TianNeurIPS
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  4. 2024PDF ↗
  5. 2024
    Continual Learning in an Open and Dynamic WorldYunhui GuoAAAI · The University of Texas at Dallas
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  6. 2024
    Evolve: Enhancing Unsupervised Continual Learning with Multiple ExpertsXiaofan Yu, Tajana Rosing, Yunhui GuoWACV · University of California San Diego
  7. 2023
    Audio-Visual Class-Incremental LearningWeiguo Pian, Shentong Mo, Yunhui Guo, Yapeng TianICCV · The University of Texas at Dallas · Carnegie Mellon University
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  8. 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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  9. 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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.