Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

3 papers of 6,984Sort Recent · Most cited
  1. 2026
    CLDIPS-CIL: Causal Learning and Dynamic Importance Parameter Selection for Class Incremental LearningJing Yang, Qinglang Li, Xiaoli Ruan … Quan ZhouIEEE Transactions · Guizhou University · Nanjing University of Posts and Telecommunications
  2. 2025
    Effective Generative Replay with Strong Memory for Continual LearningJing Yang, Xinyu Zhou, Yao He … Changfu ZhangKnowledge-Based Systems · Guizhou University · Shanghai Jiao Tong University · +2
  3. 2023
    A New Multinetwork Mean Distillation Loss Function for Open-World Domain Incremental Object DetectionJing Yang, Kun Yuan, Suhao Chen … Bin LiInternational Journal of Intelligent Systems · Guizhou University · Ministry of Education · +2
    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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.