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. 2026PDF ↗
  2. 2026
    Harness Continual Learning: Continual Adaptation Beyond Model ParametersBorui Kang, Jinrui Gu, Junhan Lv … Yang GaoarXiv
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  3. 2026
    A continual learning framework with long-term and multiple short-term memory networksShangge Liu, Lei Wang, Rui Yan … Yang GaoNeural Networks · Nanjing Tech University · University of Wollongong · +2
  4. 2025
    LibContinual: A Comprehensive Library towards Realistic Continual LearningWenbin Li, Shangge Liu, Borui Kang … Jiebo LuoarXiv
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  5. 2025PDF ↗
  6. 2025
    Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality CalibrationYiyang Chen, Tianyu Ding, Lei Wang … Wenbin LiCVPR · Nanjing University · Microsoft (United States) · +1
  7. 2024
    Continual Learning meets Multimodal Foundation Models: Fundamentals and AdvancesWenbin Li, Qi Fan, Rui Yan … Jiebo Luoon Continual Learning meets Multimodal Foundation Models:… · Nanjing University · Systems Engineering Society of China · +3
  8. 2024PDF ↗
  9. 2024
    Dynamic Replay Training for Class-Incremental LearningYan Yang, Dongdong Ren, Chenglei Peng … Yang GaoICASSP · Nanjing University · Nanjing University of Science and Technology
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.