Patents by Inventor Liren Tu

Liren Tu 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).

  • Patent number: 12189719
    Abstract: One embodiment of the present invention sets forth a technique for evaluating labeled data. The technique includes selecting, from a set of labels for a data sample, a subset of the labels representing non-outliers in a distribution of values in the set of labels. The technique also includes aggregating the subset of the labels into a benchmark for the data sample. The technique further includes generating, based on a comparison between the benchmark and an additional label, a benchmark score associated with the data sample, and generating a set of performance metrics for labeling the data sample based on the benchmark score.
    Type: Grant
    Filed: January 6, 2022
    Date of Patent: January 7, 2025
    Assignee: Scale AI, Inc.
    Inventors: Nathaniel John Herman, Akshat Bubna, Alexandr Wang, Shariq Shahab Hashme, Samuel J. Clearman, Liren Tu, Jeffrey Zhihong Li, James Lennon
  • Patent number: 11308364
    Abstract: One embodiment of the present invention sets forth a technique for evaluating labeled data. The technique includes selecting, from a set of labels for a data sample, a subset of the labels representing non-outliers in a distribution of values in the set of labels. The technique also includes aggregating the subset of the labels into a benchmark for the data sample. The technique further includes generating, based on a comparison between the benchmark and an additional label, a benchmark score associated with the data sample, and generating a set of performance metrics for labeling the data sample based on the benchmark score.
    Type: Grant
    Filed: December 30, 2019
    Date of Patent: April 19, 2022
    Assignee: SCALE AI, INC.
    Inventors: Nathaniel John Herman, Akshat Bubna, Alexandr Wang, Shariq Shahab Hashme, Samuel J. Clearman, Liren Tu, Jeffrey Zhihong Li, James Lennon