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.

10 papers of 8,653Sort Recent · Most cited
  1. 2025
    Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental LearningHao Chen, Ping Wang, Zihan Zhou … Yu–Gang JiangICCV · Shanghai Key Laboratory of Trustworthy Computing · American Public University System
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  2. 2025
    Adaptive Retention&Correction: Test-Time Training for Continual LearningHao Chen, Micah Goldblum, Zuxuan Wu, Yu–Gang JiangICLR
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  3. 2023
    Building an Open-Vocabulary Video CLIP Model With Better Architectures, Optimization and DataZuxuan Wu, Zejia Weng, Wujian Peng … Yu–Gang JiangTPAMI · Fudan University · Alpha Omega Alpha Medical Honor Society · +2
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  4. 2024
    Adaptive Rentention & Correction for Continual LearningHaoran Chen, Micah Goldblum, Zuxuan Wu, Yu-Gang JiangarXiv
  5. 2023
    PromptFusion: Decoupling Stability and Plasticity for Continual LearningHao Chen, Zuxuan Wu, Xintong Han … Yu–Gang JiangECCV
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  6. 2023PDF ↗
  7. 2022PDF ↗
  8. 2020
    M2KD: Incremental Learning via Multi-model and Multi-level Knowledge DistillationPeng Zhou, Long Mai, Jianming Zhang … Larry S. DavisBMVC · Beth Israel Deaconess Medical Center · Adobe Systems (United States) · +2
  9. 2019
    ACE: Adapting to Changing Environments for Semantic SegmentationZuxuan Wu, Xin Wang, Joseph E. Gonzalez … Larry S. DavisICCV · Berkeley College · University of California, Berkeley · +1
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  10. 2019
    M2KD: Multi-model and Multi-level Knowledge Distillation for Incremental LearningPeng Zhou, Long Mai, Jianming Zhang … Larry S. DavisarXiv
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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.