Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 8,653Sort Recent · Most cited
  1. 2021
    Co-Transport for Class-Incremental LearningDa-Wei Zhou, Han-Jia Ye, De‐Chuan ZhanACM International Conference on Multimedia · Nanjing University
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  2. 2021
    An EM Framework for Online Incremental Learning of Semantic SegmentationShipeng Yan, Jiale Zhou, Jiangwei Xie … Xuming HeACM International Conference on Multimedia · ShanghaiTech University · Shanghai Institute of Microsystem and Information Technology · +1
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  3. 2021
    When Video Classification Meets Incremental ClassesHanbin Zhao, Xin Qin, Shihao Su … Xi LiACM International Conference on Multimedia · Zhejiang University
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  4. 2021
    Remember and Reuse: Cross-Task Blind Image Quality Assessment via Relevance-aware Incremental LearningRui Ma, Hanxiao Luo, Qingbo Wu … Linfeng XuACM International Conference on Multimedia · University of Electronic Science and Technology of China
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.