Patents by Inventor Florian Luisier

Florian Luisier has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20260127377
    Abstract: Systems and methods for performing document entity extraction are described herein. The method can include receiving an inference document and a target schema. The method can also include generating one or more document inputs from the inference document and one or more schema inputs from the target schema. The method can further include, for each combination of the document input and schema input, obtaining one or more extraction inputs by generating a respective extraction input based on the combination, providing the respective extraction input to the machine-learned model, and receiving a respective output of the machine-learned model based on the respective extraction. The method can also include validating the extracted entity data based on reference spatial locations and inference spatial locations and outputting the validated extracted entity data.
    Type: Application
    Filed: January 5, 2026
    Publication date: May 7, 2026
    Inventors: Vincent Perot, Florian Luisier, Kai Kang, Ramya Sree Boppana, Jiaqi Mu, Xiaoyu Sun, Carl Elie Saroufim, Guolong Su, Hao Zhang, Nikolay Alexeevich Glushnev, Nan Hua, Yun-Hsuan Sung, Michael Yiupun Kwong
  • Patent number: 12536376
    Abstract: Systems and methods for performing document entity extraction are described herein. The method can include receiving an inference document and a target schema. The method can also include generating one or more document inputs from the inference document and one or more schema inputs from the target schema. The method can further include, for each combination of the document input and schema input, obtaining one or more extraction inputs by generating a respective extraction input based on the combination, providing the respective extraction input to the machine-learned model, and receiving a respective output of the machine-learned model based on the respective extraction. The method can also include validating the extracted entity data based on reference spatial locations and inference spatial locations and outputting the validated extracted entity data.
    Type: Grant
    Filed: August 21, 2023
    Date of Patent: January 27, 2026
    Assignee: GOOGLE LLC
    Inventors: Vincent Perot, Florian Luisier, Kai Kang, Ramya Sree Boppana, Jiaqi Mu, Xiaoyu Sun, Carl Elie Saroufim, Guolong Su, Hao Zhang, Nikolay Alexeevich Glushnev, Nan Hua, Yun-Hsuan Sung, Michael Yiupun Kwong
  • Publication number: 20250068847
    Abstract: Systems and methods for performing document entity extraction are described herein. The method can include receiving an inference document and a target schema. The method can also include generating one or more document inputs from the inference document and one or more schema inputs from the target schema. The method can further include, for each combination of the document input and schema input, obtaining one or more extraction inputs by generating a respective extraction input based on the combination, providing the respective extraction input to the machine-learned model, and receiving a respective output of the machine-learned model based on the respective extraction. The method can also include validating the extracted entity data based on reference spatial locations and inference spatial locations and outputting the validated extracted entity data.
    Type: Application
    Filed: August 21, 2023
    Publication date: February 27, 2025
    Inventors: Vincent Perot, Florian Luisier, Kai Kang, Ramya Sree Boppana, Jiaqi Mu, Xiaoyu Sun, Carl Elie Saroufim, Guolong Su, Hao Zhang, Nikolay Alexeevich Glushnev, Nan Hua, Yun-Hsuan Sung, Michael Yiupun Kwong