CLICK-THROUGH RATE MODEL AND GENERATING CUSTOMIZED COPIES USING MACHINE-LEARNED LARGE LANGUAGE MODELS

    公开(公告)号:US20240386462A1

    公开(公告)日:2024-11-21

    申请号:US18666493

    申请日:2024-05-16

    Applicant: Maplebear Inc.

    Abstract: An online system receives an indication that a user is starting an order. The online system retrieves candidate contents for the user and provides prompts to a model serving system. The model serving system is configured to provide scores for the contents based on relevancy, a likelihood of user interaction, and a likelihood of the user purchasing an item associated with the content. The online system provides scores from the model serving system to a predicted click-through rate (pCTR) model. Based on the pCTR model scores, the online system ranks the candidate contents. The online system provides content for display to the user based on the ranked candidate contents.

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