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. 2023
    Online Continual Learning on Hierarchical Label ExpansionByung Hyun Lee, Okchul Jung, Jonghyun Choi, Se Young ChunICCV · Seoul National University · Yonsei University
    PDF ↗
  2. 2023
    Cost-effective On-device Continual Learning over Memory Hierarchy with MiroXinyue Ma, Suyeon Jeong, Minjia Zhang … Myeongjae JeonAnnual International Conference on Mobile Computing and N… · Ulsan National Institute of Science and Technology · Microsoft (United States) · +1
    PDF ↗
  3. 2023
    Online Boundary-Free Continual Learning by Scheduled Data PriorHyun-woo Koh, M. Seo, Jihwan Bang … Jonghyun ChoiICLR
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.