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.

6 papers of 11,817Sort Recent · Most cited
  1. 2024
    Continual Learning for Segment Anything Model AdaptationJinglong Yang, Yichen Wu, Jun Cen … Jianguo ZhangarXiv
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  2. 2024
    Consistent Prompting for Rehearsal-Free Continual LearningZhanxin Gao, Jun Cen, Xiaobin ChangCVPR
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  3. 2022
    Learning a Condensed Frame for Memory-Efficient Video Class-Incremental LearningYixuan Pei, Zhiwu Qing, Jun Cen … Xueming QianNeurIPS
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  4. 2022
    Open-world Semantic Segmentation for LIDAR Point CloudsJun Cen, Yun, Peng, Shiwei Zhang … Mingqian TangECCV
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  5. 2021
    Conflicts between Likelihood and Knowledge Distillation in Task Incremental Learning for 3D Object DetectionYun Peng, Jun Cen, Ming LiuInternational Conference on 3D Vision (3DV) · Hong Kong University of Science and Technology
  6. 2021
    Deep Metric Learning for Open World Semantic SegmentationJun Cen, Yun Peng, Junhao Cai … Ming LiuICCV · Hong Kong University of Science and Technology · Sun Yat-sen University
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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.