Patents by Inventor Macduff Hughes

Macduff Hughes 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).

  • Contrastive Sequence-to-Sequence Data Selector
    Publication number: 20230359938
    Abstract: A method includes generating a base model by training with a first dataset of data pairs and generating an adapted model by training the base model on a second dataset of data pairs. The method also includes determining a contrastive score for each data pair of a third dataset of data pairs using the base model and the adapted model. The contrastive score is indicative of a probability of quality of the respective data pair. The method also includes training a target model using the data pairs of the third dataset and the contrastive scores.
    Type: Application
    Filed: July 12, 2023
    Publication date: November 9, 2023
    Applicant: Google LLC
    Inventors: Wei Wang, Bowen Liang, Macduff Hughes, Taro Watanabe, Tetsuji Nakagawa, Alexander Rudnick
  • Contrastive sequence-to-sequence data selector
    Patent number: 11734600
    Abstract: A method includes generating a base model by training with a first dataset of data pairs and generating an adapted model by training the base model on a second dataset of data pairs. The method also includes determining a contrastive score for each data pair of a third dataset of data pairs using the base model and the adapted model. The contrastive score is indicative of a probability of quality of the respective data pair. The method also includes training a target model using the data pairs of the third dataset and the contrastive scores.
    Type: Grant
    Filed: April 5, 2019
    Date of Patent: August 22, 2023
    Assignee: Google LLC
    Inventors: Wei Wang, Bowen Liang, Macduff Hughes, Taro Watanabe, Tetsuji Nakagawa, Alexander Rudnick
  • Contrastive Sequence-to-Sequence Data Selector
    Publication number: 20190347570
    Abstract: A method includes generating a base model by training with a first dataset of data pairs and generating an adapted model by training the base model on a second dataset of data pairs. The method also includes determining a contrastive score for each data pair of a third dataset of data pairs using the base model and the adapted model. The contrastive score is indicative of a probability of quality of the respective data pair. The method also includes training a target model using the data pairs of the third dataset and the contrastive scores.
    Type: Application
    Filed: April 5, 2019
    Publication date: November 14, 2019
    Applicant: Google LLC
    Inventors: Wei Wang, Bowen Liang, Macduff Hughes, Taro Watanabe, Tetsuji Nakagawa, Alexander Rudnick