Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2025
    Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual LearningShengqin Jiang, Tianqi Kong, Yuankai Qi … Ming-Hsuan YangarXiv
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  3. 2025
    DuPt: Rehearsal-based continual learning with dual promptsShengqin Jiang, Dao-Long Zhang, Fengna Cheng … Qingshan LiuNeural Networks
  4. 2022
    A Unified Object Counting Network With Object Occupation PriorShengqin Jiang, Qing Wang, Fengna Cheng … Qingshan LiuIEEE TCSVT · Nanjing University of Information Science and Technology · Nanjing Forestry University · +3
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  5. 2023
    Teacher Agent: A Knowledge Distillation-Free Framework for Rehearsal-Based Video Incremental LearningSheng-Qin Jiang, Yao-Huei Fang, Haokui Zhang … Peifeng WangInternational Journal of Computer Vision
    PDF ↗
  6. 2016
    Spatially Regularized Streaming Sensor SelectionChangsheng Li, Wei Fan, Weishan Dong … Xin ZhangAAAI · IBM Research (China) · Stanford 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 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.