Patents by Inventor Zeqiu WU

Zeqiu WU 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: 20230325603
    Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.
    Type: Application
    Filed: June 13, 2023
    Publication date: October 12, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Michel GALLEY, Christopher Brian QUIRK, William Brennan DOLAN, Zeqiu WU
  • Patent number: 11741306
    Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.
    Type: Grant
    Filed: March 12, 2020
    Date of Patent: August 29, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Michel Galley, Christopher Brian Quirk, William Brennan Dolan, Zeqiu Wu
  • Publication number: 20220164520
    Abstract: Systems and method directed to assistive document generation are described. More specifically, similar documents share large portions of reusable text structures that can be used to generate an initial document thereby saving a user time. To generate the document, an indication to create the document may be received and based on the indication, a plurality of example documents and grounding content may be identified. Example documents may be existing documents that are similar to a target document of the writer. Grounding information may refer to content that is relevant, timely, and accurate when applied to the target document. The plurality of example documents and the grounding content may be received, and a document sketch based on the example documents and the grounding content may be generated and contains a plurality of predicted text sequences based on the example documents and the grounding content.
    Type: Application
    Filed: January 11, 2021
    Publication date: May 26, 2022
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: William B. DOLAN, Zeqiu WU, Michel GALLEY, Yizhe ZHANG, Zhang LI, Christopher John BROCKETT
  • Publication number: 20210192140
    Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.
    Type: Application
    Filed: March 12, 2020
    Publication date: June 24, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Michel GALLEY, Christopher Brian QUIRK, William Brennan DOLAN, Zeqiu WU