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.

11 papers of 8,653Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026
    AdaEvol: Dynamic Adapter Merging for Effective Continual Learning and Knowledge Transfer in Large Language ModelsR X Liu, Min Yu, Jianguo Jiang … Ming LiuICASSP · Chinese Academy of Sciences · Institute of Information Engineering · +2
  3. 2023
    Learning to learn for few-shot continual active learningStella Ho, Ming Liu, Shang Gao, Longxiang GaoArtificial Intelligence Review · Deakin University · The University of Melbourne · +1
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  4. 2021
    Prototype-Guided Memory Replay for Continual LearningStella Ho, Ming Liu, Lan Du … Yong XiangTNNLS · Deakin University · Monash University · +1
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  5. 2022
    Semi-supervised Continual Learning with Meta Self-trainingStella Ho, Ming Liu, Lan Du … Shang GaoACM International Conference on Information & Knowled… · Deakin University · Monash University · +1
  6. 2022
    Open-world Semantic Segmentation for LIDAR Point CloudsJun Cen, Yun, Peng, Shiwei Zhang … Mingqian TangECCV
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  7. 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
  8. 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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  9. 2021
    In Defense of Knowledge Distillation for Task Incremental Learning and Its Application in 3D Object DetectionYun Peng, Yuxuan Liu, Ming LiuRA-L · Hong Kong University of Science and Technology
  10. 2021
    Prototypes-Guided Memory Replay for Continual LearningStella Ho, Ming Liu, Lan Du … Yong XiangarXiv
  11. 2021
    MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningMarcin Andrychowicz, Misha Denil, Sergio Gómez … Longxiang GaoPreprint
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.