Patents by Inventor Orrin Naylor

Orrin Naylor 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).

  • Using a visual language model and a generative artificial intelligence model to evaluate and correct an image of a collection of items
    Patent number: 12664706
    Abstract: An online system generates images for collections of items using an image generation model. To ensure a generated image accurately reflects a collection of items, the online system determines a type of the collection and selects a template including evaluation questions associated with the determined type. Evaluation questions are curated to determine accuracy of the content of a generated image for the collection. By applying a visual learning model to the questions in the selected template and the generated image, the online system identifies discrepancies between the image and the collection of items from the output of the vision language model. Subsequently, the online system prompts the image generation model to create an updated image for the collection that does not include the identified discrepancies. The online system may repeat the discrepancy identification and image modification until no discrepancies are found in the generated image.
    Type: Grant
    Filed: August 28, 2024
    Date of Patent: June 23, 2026
    Assignee: Maplebear Inc.
    Inventors: Prithvishankar Srinivasan, Orrin Naylor, Jatin Jain, Shishir Kumar Prasad, Katherine Tsen, Riddhima Sejpal
  • USING A VISUAL LANGUAGE MODEL AND A GENERATIVE ARTIFICIAL INTELLIGENCE MODEL TO EVALUATE AND CORRECT AN IMAGE OF A COLLECTION OF ITEMS
    Publication number: 20260065545
    Abstract: An online system generates images for collections of items using an image generation model. To ensure a generated image accurately reflects a collection of items, the online system determines a type of the collection and selects a template including evaluation questions associated with the determined type. Evaluation questions are curated to determine accuracy of the content of a generated image for the collection. By applying a visual learning model to the questions in the selected template and the generated image, the online system identifies discrepancies between the image and the collection of items from the output of the vision language model. Subsequently, the online system prompts the image generation model to create an updated image for the collection that does not include the identified discrepancies. The online system may repeat the discrepancy identification and image modification until no discrepancies are found in the generated image.
    Type: Application
    Filed: August 28, 2024
    Publication date: March 5, 2026
    Inventors: Prithvishankar Srinivasan, Orrin Naylor, Jatin Jain, Shishir Kumar Prasad, Katherine Tsen, Riddhima Sejpal