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Volume 9 Issue 11
Nov.  2022

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2022  >  9(11): 2031-2033
B. Liu, R. Y. Song, Y. J. Xiang, J. B. Du, W. J. Ruan, and J. H. Hu, “Self-supervised entity alignment based on multi-modal contrastive learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2031–2033, Nov. 2022. doi: 10.1109/JAS.2022.105962
Citation: B. Liu, R. Y. Song, Y. J. Xiang, J. B. Du, W. J. Ruan, and J. H. Hu, “Self-supervised entity alignment based on multi-modal contrastive learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2031–2033, Nov. 2022. doi: 10.1109/JAS.2022.105962
shu

Self-Supervised Entity Alignment Based on Multi- Modal Contrastive Learning

doi: 10.1109/JAS.2022.105962
  • 1.

    School of Software Engineering, Xi’an Jiaotong University, Xi’an 710000, and also with the China Electronics Technology Group Corporation (CETC) Key Laboratory of Smart City Model Simulation and Intelligent Technology, the Smart City Research Institute of CETC and National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518000, China

  • 2.

    Chinese University of Hong Kong, Shenzhen 518000, China

  • 3.

    Tencent, Shenzhen 518000, China

  • 4.

    CETC Key Laboratory of Smart City Model Simulation and Intelligent Technology, the Smart City Research Institute of CETC and National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518000, China

  • 5.

    Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, and also with the CETC Key Laboratory of Smart City Model Simulation and Intelligent Technology, the Smart City Research Institute of CETC and National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518000, China

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    • References(12)
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