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.

3 papers of 11,817Sort Recent · Most cited
  1. 2026
    Dynamic Prompt Synthesis Via Global Codebook Aggregation and Residual Compensation for Continual LearningYong Dai, Haijun Liu, Yingping Zhao, Jinfeng YangInternational Symposium on Robotics, Artificial Intellige…
  2. 2025
    Fine-Grained Prompt Tuning via Dynamic Weighting for Continual LearningHaijun Liu, Zhi-Tao Wu, Yingping Zhao … Jinfeng YangInternational Conference on Algorithm, Image Processing a…
  3. 2023
    MDL-NAS: A Joint Multi-domain Learning Framework for Vision TransformerShiguang Wang, Tao Xie, Jian Cheng … Haijun LiuCVPR
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.