公开(公告)号：US20240289861A1

公开(公告)日：2024-08-29

申请号：US18587655

申请日：2024-02-26

Applicant: Maplebear Inc.

Inventor： Haixun Wang ,  Tejaswi Tenneti ,  Taesik Na ,  Yuanzheng Zhu ,  Vinesh Reddy Gudla ,  Lee Cohn

IPC: G06Q30/0601

CPC classification number: G06Q30/0631 ,  G06Q30/0627 ,  G06Q30/0635 ,  G06Q30/0643

Abstract: Responsive to an input query from a user, an online system presents a list of recommended items that are related to the input query. The input query may be formulated as a natural language query. The online system performs an inference task in conjunction with the model serving system to generate one or more additional queries that are related to the input query and/or are otherwise related to the recommended items presented in response to the input query. The additional queries may be presented to the user in conjunction with the list of recommended items.

公开(公告)号：US20250156451A1

公开(公告)日：2025-05-15

申请号：US18510565

申请日：2023-11-15

Applicant: Maplebear Inc.

Inventor： Jacob Jensen ,  Fei Jia ,  Esther Vasiete Allas ,  Manmeet Singh ,  Lee Cohn ,  Tejaswi Tenneti

IPC: G06F16/332 ,  G06F40/284 ,  G06F40/40

Abstract: A language model is used to generate autosuggestions to complete or revise a user's partial search query. An initial partial query is applied to the language model to generate query candidates for completing the search query. The language model may generate the query candidates as additional or alternate tokens for the partial search query. When the user revises the partial query, the previously-generated candidates can be re-used to reduce subsequent processing time for generating additional candidates. The previously-generated candidates are compared with the revised partial query to select which of the candidates to be re-used and expanded for generating additional tokens. Additional tokens can be generated in parallel for the previously-generated candidates or with model values from the previous generation, enabling the tokens to be generated effectively with reduced latency consistent with user expectations for search-related autosuggestions.