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. 2025
    Feature Dispersion Adaptation With Pre-Pooling Prototype for Continual Image ClassificationWuxuan Shi, Mang Ye, Wei Yu, Bo DuIEEE Trans. Multimedia · Wuhan University
  2. 2025
    BiaMix Contrastive Learning and Memory Similarity Distillation in Class-Incremental LearningMang Ye, Wenke Huang, Zekun Shi … Bo DuCAAI Transactions on Intelligence Technology · Wuhan University · Hubei University of Technology
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  3. 2025
    Synthetic Data is an Elegant GIFT for Continual Vision-Language ModelsWu Bin, Wuxuan Shi, Jinqiao Wang, Mang YeCVPR · Wuhan University · Chinese Academy of Sciences · +1
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  4. 2025PDF ↗
  5. 2025
    MOTION: Multi-Sculpt Evolutionary Coarsening for Federated Continual Graph LearningFrank Wan, Fengyuan Ran, Ruikang Zhang … Mang YeNeurIPS · Wuhan University · Tongji University · +2
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.