公开(公告)号：US20230113019A1

公开(公告)日：2023-04-13

申请号：US18080549

申请日：2022-12-13

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD

Inventor： Hanyu PENG ,  Weiguo PIAN ,  Mingming SUN ,  Ping LI

IPC: G06N20/00

Abstract: A method for generating a model includes: obtaining training data for training a target model, in which the training data includes labeled data and unlabeled data; obtaining a first output result by the target model based on the labeled data; obtaining a second output result by the target model based on the unlabeled data; and obtaining an optimized target model by optimizing the target model based on the first output result and the second output result.

公开(公告)号：US20250095250A1

公开(公告)日：2025-03-20

申请号：US18749438

申请日：2024-06-20

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

Inventor： Haoran WANG ,  Zeke XIE ,  Yunfeng CAI ,  Mingming SUN

IPC: G06T11/60 ,  G06T9/00 ,  G06V10/44

Abstract: A method is provided that includes: obtaining a reference image and a description text; extracting a text feature of the description text; and performing the following operations based on a pre-trained diffusion model to generate a target image: in each time step of the diffusion model: calculating a first cross-attention feature of a first image feature and the text feature; obtaining a second cross-attention feature of a second image feature of the reference image and the text feature; editing the first cross-attention feature based on the second cross-attention feature to obtain a third cross-attention feature; and generating a result image feature of the time step based on the third cross-attention feature and the text feature; and decoding a result image feature of a last time step to generate the target image.

公开(公告)号：US20240411979A1

公开(公告)日：2024-12-12

申请号：US18749479

申请日：2024-06-20

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

Inventor： Minlong PENG ,  Mingming SUN ,  Yabing SHI

IPC: G06F40/10 ,  G06N3/08

Abstract: A method, apparatus, device, and medium for determining the similarity of text processing tasks is provided. The method includes: determining a first task, a second task, and a neural network, the neural network includes a plurality of network modules and a plurality of importance coefficients corresponding to the plurality of network modules, and the importance coefficients are used to scale output values of a corresponding network module; respectively performing a target operation using the first task and the second task as a target task to obtain an embedding feature of the first task and an embedding feature of the second task; and determining the task similarity between the first task and the second task based on the embedding features. The target operation includes: training using text samples and obtaining a plurality of trained importance coefficients; and determining an embedding feature of the target task based on trained importance coefficients.

公开(公告)号：US20230274161A1

公开(公告)日：2023-08-31

申请号：US17940059

申请日：2022-09-08

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

Inventor： Jinxing YU ,  Minlong PENG ,  Mingming SUN ,  Ping LI

IPC: G06N5/02 ,  G06F16/903

CPC classification number: G06N5/022 ,  G06F16/90335

Abstract: There is provided an entity linking method, an electronic device, and a storage medium, which relates to the technical field of artificial intelligence such as machine learning, natural language processing, and intelligent search. A specific implementation solution involves: acquiring a target entity in a knowledge base and most relevant to a to-be-linked entity in a specified statement; and deciding, based on a linking decision strategy, whether to link the to-be-linked entity to the target entity in the knowledge base.

公开(公告)号：US20230273932A1

公开(公告)日：2023-08-31

申请号：US17947659

申请日：2022-09-19

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

Inventor： Xu LI ,  Yunfeng CAI ,  Mingming SUN ,  Ping LI

IPC: G06F16/2458 ,  G06F16/22

CPC classification number: G06F16/2465 ,  G06F16/2237

Abstract: A method for discovering causality from data includes acquiring to-be-processed data, and obtaining a covariance matrix of the to-be-processed data; determining a first target column in the covariance matrix, taking the number of columns of the first target column as a first place in a rearrangement sequence, and obtaining a first upper triangular matrix according to the first target column; determining a position of the number of columns of the covariance matrix other than the first target column except the first place in the rearrangement sequence according to the first target column and the first upper triangular matrix, and obtaining an upper triangular matrix in each position determination; obtaining an adjacency matrix according to an upper triangular matrix and a rearrangement sequence obtained in final position determination; and generating directed acyclic graph (DAG) by using the adjacency matrix, and taking the DAG as causality discovery result of the to-be-processed data.

公开(公告)号：US20230274088A1

公开(公告)日：2023-08-31

申请号：US17942116

申请日：2022-09-10

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

Inventor： Minlong PENG ,  Mingming SUN ,  Ping LI

IPC: G06F40/211

CPC classification number: G06F40/211

Abstract: There is provided a sentiment parsing method and apparatus, an electronic device, and a storage medium, which relates to the technical field of artificial intelligence such as machine learning and natural language processing. A specific implementation solution involves: identifying a role of a sentiment parsing object in a specified statement; trimming the specified statement based on the role of the sentiment parsing object to acquire pruning result information after the trimming; and parsing sentiment of the sentiment parsing object in the specified statement based on the pruning result information.