公开(公告)号：US11526557B2

公开(公告)日：2022-12-13

申请号：US16697979

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Zhiguo Wang ,  Zhiheng Huang ,  Ramesh M. Nallapati ,  Bing Xiang

IPC: G06F16/9038 ,  G06F16/908 ,  G06F16/93 ,  G06N20/00

Abstract: Techniques for displaying a search are described. An exemplary method includes receiving a search query, performing the search query on a plurality of documents, the documents including text passages, to generate a search query result, determining an aspect of the search query result that has a confidence value that exceeds a first confidence threshold with respect to its relevance to the search query; and, displaying the search result including an emphasis on the aspect of the result exceeds the first confidence threshold.

公开(公告)号：US20250111267A1

公开(公告)日：2025-04-03

申请号：US18478811

申请日：2023-09-29

Applicant: Amazon Technologies, Inc.

Inventor： Zhiheng Huang ,  Yue Yang ,  Lan Liu ,  Yuhao Zhang ,  Peng Qi

IPC: G06N20/00 ,  G06F40/30 ,  G06F40/40

Abstract: Template-based tuning is performed on a generative machine learning model where a shared template is used to tune the generative machine learning model across multiple natural language tasks. When a natural language request to perform a natural language task is received, portions of a shared template to complete are identified as part of generating a prompt. The generative machine learning model is instructed according to the generated prompt and a response to the request is returned based on a result of the generative machine learning model.

公开(公告)号：US11366855B2

公开(公告)日：2022-06-21

申请号：US16697948

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Jean-Pierre Dodel ,  Zhiheng Huang ,  Xiaofei Ma ,  Ramesh M. Nallapati ,  Krishnakumar Rajagopalan ,  Milan Saini ,  Sudipta Sengupta ,  Saurabh Kumar Singh ,  Dimitrios Soulios ,  Ankit Sultania ,  Dong Wang ,  Zhiguo Wang ,  Bing Xiang ,  Peng Xu ,  Yong Yuan

IPC: G06F16/00 ,  G06F16/901 ,  G06N3/04 ,  G06F16/2457 ,  G06F16/903

Abstract: Techniques for searching documents are described. An exemplary method includes receiving a document search query; querying at least one index based upon the document search query to identify matching data; fetching the identified matched data; determining one or more of a top ranked passage and top ranked documents from the set of documents based upon one or more invocations of one or more machine learning models based at least on the fetched identified matched data and the document search query; and returning one or more of the top ranked passage and the proper subset of documents.

公开(公告)号：US20250111151A1

公开(公告)日：2025-04-03

申请号：US18477209

申请日：2023-09-28

Applicant: Amazon Technologies, Inc.

Inventor： Zhiheng Huang ,  Yue Yang ,  Lan Liu

IPC: G06F40/205 ,  G06F40/284 ,  G06N3/0455

Abstract: An index is created with split documents to retrieve and augment generation of a response to a natural language request using a generative machine learning model. When a natural language request is received, a search representation is generated and used to retrieve candidate portions of documents from the index. A relevancy ranking is performed to identify relevant portions of documents from the candidates and provide the relevant portions to prompt a generative machine learning model to provide a result for the natural language request.