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.

6 papers of 8,653Sort Recent · Most cited
  1. 2021
    Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear ConnectorGuoliang Lin, Hanlu Chu, Hanjiang LaiCVPR · Sun Yat-sen University · South China Normal University
    PDF ↗
  2. 2021
    Discriminative Distillation to Reduce Class Confusion in Continual LearningChanghong Zhong, Zhiying Cui, Wei‐Shi Zheng … Ruixuan WangSpringer LNCS · Sun Yat-sen University · Key Laboratory of Guangdong Province
    PDF ↗
  3. 2021
    Secure and efficient parameters aggregation protocol for federated incremental learning and its applicationsXiaoying Wang, Zhiwei Liang, Arthur Sandor Voundi Koe … Qintai YangInternational Journal of Intelligent Systems · Sun Yat-sen University · Third Affiliated Hospital of Sun Yat-sen University · +1
  4. 2021
    Blind Adaptive Gait Planning on Non-stationary Environments via Continual Reinforcement LearningHao Hu, Yang LiuIEEE International Conference on Unmanned Systems (ICUS) · Sun Yat-sen University
  5. 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
    PDF ↗
  6. 2021
    Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and MaskingBinzong Geng, Fajie Yuan, Qiancheng Xu … Min YangACL · University of Science and Technology of China · Chinese Academy of Sciences · +7
    PDF ↗
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.