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.

7 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
    Distribution and expression aware retrospective learning for single-cell long-tailed class-incremental annotationTian-Hao Li, Zi-Xuan Wang, Chen-Peng Wu … Yong-Qing ZhangApplied Soft Computing
  3. 2025PDF ↗
  4. 2025
    T2I-ConBench: Text-to-Image Benchmark for Continual Post-trainingZhehao Huang, Yuhang Liu, Yixin Lou … Xiaolin HuangarXiv
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  5. 2025PDF ↗
  6. 2025
    Coreset Selection via Reducible Loss in Continual LearningRuilin Tong, Yuhang Liu, J. Shi, Dong GongICLR
  7. 2022
    Learning Bayesian Sparse Networks with Full Experience Replay for Continual LearningQingsen Yan, Dong Gong, Yuhang Liu … Qinfeng ShiCVPR · Australian Centre for Robotic Vision · The University of Adelaide · +1
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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.