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.

5 papers of 6,984Sort Recent · Most cited
  1. 2026
    Elastic Multi-Gradient Descent for Parallel Continual LearningFan Lyu, Wei Feng, Yuepan Li … Liang WangTPAMI · Universitat Autònoma de Barcelona · Tianjin University · +2
    PDF ↗
  2. 2026
    Dual Domain-Attribute Learning Framework With Asynchronous Adapters for Continual Test-Time AdaptationYuntong Tian, Kang Li, Tianyang He … Wei FengTIP · Tianjin University · University of Electronic Science and Technology of China · +1
  3. 2025
    FedAGC: Federated Continual Learning with Asymmetric Gradient CorrectionC T Zhang, Fanhua Shang, Hongyin Liu … Wei FengICCV · Tianjin University · Tianjin Medical University
  4. 2025
    Beyond Background Shift: Rethinking Instance Replay in Continual Semantic SegmentationHongmei Yin, Tingliang Feng, Fan Lyu … Liang WanCVPR · Tianjin University · Institute of Automation
    PDF ↗
  5. 2023
    Measuring Asymmetric Gradient Discrepancy in Parallel Continual LearningFan Lyu, Qing Sun, Fanhua Shang … Wei FengICCV · Tianjin University
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.