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.

7 papers of 11,817Sort Recent · Most cited
  1. 2020
    I3DOL: Incremental 3D Object Learning without Catastrophic ForgettingJiahua Dong, Yang Cong, Gan Sun … Lichen WangAAAI · Shenyang Institute of Automation · University of Chinese Academy of Sciences · +2
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  2. 2020
    State Primitive Learning to Overcome Catastrophic Forgetting in RoboticsFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Hong QiaoCognitive Computation · Shandong Institute of Automation · University of Chinese Academy of Sciences · +2
  3. 2020
    Continual Domain Adaptation for Machine Reading ComprehensionLixin Su, Jiafeng Guo, Ruqing Zhang … Xueqi ChengCIKM · Computer Network Information Center · University of Chinese Academy of Sciences
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  4. 2020
    Learning Stable Control for a Wheeled Inverted Pendulum with Fast Adaptive Neural NetworkYuanzhe Peng, Yongsheng Ou, Wei FengIEEE International Conference on Real-time Computing and… · Chinese Academy of Sciences · Shenzhen Institutes of Advanced Technology · +1
  5. 2020
    Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learningFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Amir HussainNeural Networks · Shandong Institute of Automation · Institute of Automation · +7
  6. 2020
    OSCD: A one-shot conditional object detection frameworkKun Fu, Tengfei Zhang, Yue Zhang, Xian SunNeurocomputing · Chinese Academy of Sciences · Institute of Electronics · +2
  7. 2020
    Distill and Replay for Continual Language LearningJingyuan Sun, Shaonan Wang, Jiajun Zhang, Chengqing ZongCOLING · Institute of Automation · University of Chinese Academy of Sciences · +2
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.