METHODS AND SYSTEMS FOR DYNAMIC GENERATION OF PERSONALIZED TEXT USING LARGE LANGUAGE MODEL

    公开(公告)号:US20240256792A1

    公开(公告)日:2024-08-01

    申请号:US18180545

    申请日:2023-03-08

    Applicant: Shopify Inc.

    CPC classification number: G06F40/40 G06F16/337

    Abstract: Methods and systems for automatically prompting a LLM to generate a personalized text, such as a personalized textual description, in which portions of the text are customized based on user attributes. In various examples, responsive to a request for a textual description, a user record is retrieved for a user associated with the request and one or more user attributes are obtained based on the user record. In examples, a prompt to a large language model (LLM) for generating a user-specific textual description is generated, the prompt including the one or more user attributes to include in the generated user-specific textual description and a source text. The prompt is provided to the LLM to receive a generated user-specific textual description. The generated user-specific textual description is provided for display via a user device.

    METHODS AND SYSTEMS FOR GENERATION OF TEXT USING LARGE LANGUAGE MODEL WITH INDICATIONS OF UNSUBSTANTIATED INFORMATION

    公开(公告)号:US20240256764A1

    公开(公告)日:2024-08-01

    申请号:US18180518

    申请日:2023-03-08

    Applicant: Shopify Inc.

    CPC classification number: G06F40/169 G06F16/3328 G06F40/205 G06F40/40

    Abstract: Methods and systems for prompting a large language model (LLM) to generate a description of an object with indications of any unsubstantiated information are disclosed. A prompt is generated to a LLM to generate a description of an object, where the prompt includes one or more object attributes to include in the generated description. The prompt also includes an instruction for the LLM to annotate any portions of the generated description that are, involve, and/or include unsubstantiated information according to a defined format. The prompt is provided to the LLM and the generated description is received. The generated description is parsed to identify, based on the defined format, one or more annotated portions indicating unsubstantiated information. The generated description is presented for display via a user device.

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