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.

9 papers of 11,817Sort Recent · Most cited
  1. 2024PDF ↗
  2. 2024
    Analogical Learning-Based Few-Shot Class-Incremental LearningJiashuo Li, Songlin Dong, Yihong Gong … Xing WeiIEEE TCSVT
  3. 2024
  4. 2024
    Analogical Augmentation and Significance Analysis for Online Task-Free Continual LearningSonglin Dong, Yingjie Chen, Yuhang He … Yihong GongIEEE Trans. Multimedia
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  5. 2024
    Non-exemplar Domain Incremental Object Detection via Learning Domain BiasXiang Song, Yuhang He, Songlin Dong, Yihong GongAAAI
  6. 2024PDF ↗
  7. 2024
    Overcoming Catastrophic Forgetting for Multi-Label Class-Incremental LearningXiang Song, Kuang Shu, Songlin Dong … Yihong GongWACV
  8. 2024
    Domain Incremental Object Detection Based on Feature Space Topology Preserving StrategyLiping Ding, Xiang Song, Yuhang He … Yihong GongIEEE TCSVT
  9. 2024
    Non-exemplar Domain Incremental Learning via Cross-Domain Concept IntegrationQiang Wang, Yuhang He, Songlin Dong … Yihong GongECCV
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.