The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 27, 2026

Filed:

Aug. 21, 2023
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Vincent Perot, Brooklyn, NY (US);

Florian Luisier, Boston, MA (US);

Kai Kang, Seattle, WA (US);

Ramya Sree Boppana, Sunnyvale, CA (US);

Jiaqi Mu, Sunnyvale, CA (US);

Xiaoyu Sun, Sunnyvale, CA (US);

Carl Elie Saroufim, San Francisco, CA (US);

Guolong Su, Houston, TX (US);

Hao Zhang, Jersey City, NJ (US);

Nikolay Alexeevich Glushnev, Woondinville, WA (US);

Nan Hua, Palo Alto, CA (US);

Yun-Hsuan Sung, San Francisco, CA (US);

Michael Yiupun Kwong, Mountain View, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/295 (2020.01); G06V 30/19 (2022.01);
U.S. Cl.
CPC ...
G06F 40/295 (2020.01); G06V 30/19147 (2022.01);
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.


Find Patent Forward Citations

Perot, Vincent. (2026). Document entity extraction using machine-learned models (U.S. Patent No. 12536376). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12536376

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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