公开(公告)号：US20230080904A1

公开(公告)日：2023-03-16

申请号：US18054608

申请日：2022-11-11

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Yaqian HAN ,  Shuohuan WANG ,  Yu SUN

IPC: G06F40/30 ,  G06N5/02

Abstract: A method for generating a cross-lingual textual semantic model includes: acquiring a set of training data that includes pieces of monolingual non-parallel text and pieces of bilingual parallel text; determining a semantic vector of each piece of text in the set of training data by inputting each piece of text into an initial textual semantic model; determining a distance between semantic vectors of each two pieces of text in the set of training data based on the semantic vector of each piece of text in the set of training data; determining a gradient modification based on a parallel relationship between each two pieces of text in the set of training data and the distance between the semantic vectors of each two pieces of text in the set of training data; and acquiring a modified textual semantic model by modifying the initial textual semantic model based on the gradient modification.

公开(公告)号：US20230206080A1

公开(公告)日：2023-06-29

申请号：US18118339

申请日：2023-03-07

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Shuohuan WANG ,  Weibao GONG ,  Zhihua WU ,  Yu SUN ,  Siyu DING ,  Yaqian HAN ,  Yanbin ZHAO ,  Yuang LIU ,  Dianhai YU

IPC: G06N3/094 ,  G06N3/045

CPC classification number: G06N3/094 ,  G06N3/045

Abstract: A model training system includes at least one first cluster and a second cluster communicating with the at least first cluster. The at least one first cluster is configured to acquire a sample data set, generate training data according to the sample data set, and send the training data to the second cluster; and the second cluster is configured to train a pre-trained model according to the training data sent by the at least one first cluster.