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. 2025PDF ↗
  2. 2025
    Max-Informative Unlabeled Sample Replay for Semi-Supervised Class-Incremental Learning in Audio ClassificationQiang Wang, Ao Shen, Da-Wei Feng … Huaimin WangFall Joint Computer Conference
  3. 2025PDF ↗
  4. 2025
    A complex electromagnetic signal class incremental learning method based on constrained replay and dynamic neuronsWei Zhang, Guolong Cui, Guanglong Ren … Jian CuiJournal of Systems Engineering and Electronics
  5. 2022
    FIG-LP: Feature-Inverse-Graph based Link Prediction in Graph StreamXu Zhang, Xiao-Qiang Xiao, Guowei Li … Jiantong SongIEEE Smartworld, Ubiquitous Intelligence & Computing,… · National University of Defense Technology · Changsha University
  6. 2019
    Label Mapping Neural Networks with Response Consolidation for Class Incremental LearningXu Zhang, Yao Yang, Baile Xu … Qingwei LinarXiv · Nanjing University · Microsoft Research (United Kingdom)
    PDF ↗
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.