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.

8 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026PDF ↗
  3. 2025
    Specifying What You Know or Not for Multi-Label Class-Incremental LearningAoting Zhang, Dongbao Yang, Chang Liu … Yu ZHOUAAAI
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  4. 2025
    DCA: Dividing and Conquering Amnesia in Incremental Object DetectionAoting Zhang, Dongbao Yang, Chang Liu … Yu ZHOUAAAI
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  5. 2023
    Pseudo Object Replay and Mining for Incremental Object DetectionDongbao Yang, Yu ZHOU, Xiaopeng Hong … Weipinng WangACM MM
  6. 2021
    Multi-View Correlation Distillation for Incremental Object DetectionDongbao Yang, Yu Zhou, Aoting Zhang … Qixiang YePattern Recognition · Chinese Academy of Sciences · Institute of Information Engineering · +1
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  7. 2022
    RD-IOD: Two-Level Residual-Distillation-Based Triple-Network for Incremental Object DetectionDongbao Yang, Yu Zhou, Wei Shi … Weiping WangACM Transactions · University of Chinese Academy of Sciences · Chinese Academy of Sciences · +1
  8. 2020PDF ↗
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.