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公开(公告)号：US20210192364A1
公开(公告)日：2021-06-24
申请号：US17124030
申请日：2020-12-16
Inventor： Haifeng WANG , Wenbin JIANG , Yajuan LV , Yong ZHU , Hua WU
IPC: G06N5/02 , G06F40/30 , G06F40/279 , G06K9/62
Abstract: The present application discloses a text processing method and device based on natural language processing and a knowledge graph, and relates to the in-depth field of artificial intelligence technology. A specific implementation is: an electronic device uses a joint learning model to obtain a semantic representation, which is obtained by the joint learning model by combining knowledge graph representation learning and natural language representation learning, it combines a knowledge graph representation learning and a natural language representation learning, compared to using only the knowledge graph representation learning or the natural language representation learning to learn semantic representation of a prediction object, factors considered by the joint learning model are more in quantity and comprehensiveness, so accuracy of semantic representation can be improved, and thus accuracy of text processing can be improved.
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公开(公告)号：US20210192142A1
公开(公告)日：2021-06-24
申请号：US17024756
申请日：2020-09-18
Inventor： Zhifan FENG , Haifeng WANG , Kexin REN , Yong ZHU , Yajuan LYU
Abstract: The present disclosure discloses a multimodal content processing method, apparatus, device and storage medium, which relate to the technical field of artificial intelligence. The specific implementation is: receiving a content processing request of a user which is configured to request semantic understanding of multimodal content to be processed, analyzing the multimodal content to obtain the multimodal knowledge nodes corresponding to the multimodal content, determining a semantic understanding result of the multimodal content according to the multimodal knowledge nodes, a pre-constructed multimodal knowledge graph and the multimodal content, the multimodal knowledge graph including: the multimodal knowledge nodes and an association relationship between multimodal knowledge nodes. The technical solution can obtain an accurate semantic understanding result, realize an accurate application of multimodal content, and solve the problem in the prior art that multimodal content understanding is inaccurate.
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43.发明申请公开(公告)号：US20250094460A1
公开(公告)日：2025-03-20
申请号：US18969597
申请日：2024-12-05
Inventor： Haifeng WANG , Hua WU , Hao TIAN , Jing LIU , Ruiqing ZHANG , Yan CHEN , Yu RAN
IPC: G06F16/3329 , G06F16/3332 , G06F16/334
Abstract: A query answering method, an electronic device, a storage medium, and an intelligent agent are provided, which relate to a field of artificial intelligence technology, and in particular to fields of large model, intelligent search and information processing technology. The method includes: inputting, in response to a retrieval content set retrieved based on a query, the query, the retrieval content set and prompt information for answer generation into the large model, so that the large model performs operations of: processing, based on a current task in the prompt information and the query, a current text corresponding to the retrieval content set to obtain a processed text, where the current task is determined based on a task execution order in the prompt information; and obtaining, in a case of determining that the processed text meets a preset condition, an answer to the query based on the processed text.
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公开(公告)号：US20250061305A1
公开(公告)日：2025-02-20
申请号：US18936686
申请日：2024-11-04
Inventor： Shuohuan WANG , Junyuan SHANG , Yinqi YANG , Guoxia WANG , Linhao ZHANG , Yu SUN , Hua WU , Haifeng WANG
IPC: G06N3/043 , G06N3/045 , G06N3/0985
Abstract: A training method, an inference method, a device, an apparatus, and a medium for a deep learning model are provided. A first model includes a plurality of first parameters, a second model comprises a plurality of second parameters, which is initialized to parameter values of a plurality of target parameters selected from the plurality of first parameters. The training method includes: determining a target loss for both the first model and the second model; adjusting parameter values, including: in response to determining that the target loss indicates that the parameter values of at least part of the target parameters need to be adjusted, synchronously adjusting the parameter values of the corresponding second parameters; and in response to determining that the target loss indicates that the parameter values of at least part of the second parameters need to be adjusted, synchronously adjusting the parameter values of the corresponding target parameters.
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公开(公告)号：US20240394190A1
公开(公告)日：2024-11-28
申请号：US18696757
申请日：2022-09-27
Inventor： Minxu ZHANG , Haifeng WANG , Fan ZHANG , Xinxuan WU , Xuefeng YAO , Danlei FENG , Zhihua WU , Zhipeng TAN , Jie DING , Dianhai YU
IPC: G06F12/0873 , G06F12/0815 , G06F15/80
Abstract: The present application provides a method of training a deep learning model. A specific implementation solution of the method of training the deep learning model includes: determining, according to first training data for a current training round, a first target parameter required to be written into a target memory in a first network parameter required by an embedding of the first training data, wherein the target memory is a memory contained in a target processor; determining a remaining storage slot in the target memory according to a first mapping relationship between a storage slot of the target memory and a network parameter; and writing, in response to the remaining storage slot meeting a storage requirement of the first target parameter, the first target parameter into the target memory so that a computing core contained in the target processor adjusts the first network parameter according to the first training data.
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Patent Agency Ranking
公开(公告)号：US20240185379A1
公开(公告)日：2024-06-06
申请号：US17758692
申请日：2021-11-17
Inventor： Deguo XIA , Jizhou HUANG , Haifeng WANG
Abstract: A method and an apparatus for generation a high definition map, a device and a computer storage medium, which relate to automatic driving and deep learning technologies in the field of artificial intelligence technologies, are disclosed. An implementation includes: acquiring point cloud data and front-view image data which are collected respectively by a plurality of collecting devices at a plurality of location points to obtain a sequence of point clouds and a sequence of front-view images; performing registration of the front-view images and the point clouds on the sequence of point clouds and the sequence of front-view images; transforming the sequence of front-view images into a top-view image based on the result of the registration and determining coordinate information of each pixel in the top-view image; and identifying map elements of the top-view image to obtain the high definition map.
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公开(公告)号：US20230041943A1
公开(公告)日：2023-02-09
申请号：US17961930
申请日：2022-10-07
Inventor： Deguo XIA , Jizhou HUANG , Haifeng WANG
IPC: G01C21/00
Abstract: The present disclosure provides a method and apparatus for automatically producing map data. The method includes: performing track rectification on crowdsourcing tracks based on corresponding standard tracks, and locating each map element included, based on depth information of track point images included in the rectified crowdsourcing tracks; comparing a latest map element obtained based on the rectified crowdsourcing tracks locating and an old map element at a corresponding locating position using a pre-built entity semantic map; determining, in response to a change in the latest map element compared to the old map element, a target processing method according to a processing standard of a changed map element pre-abstracted from a map element update specification; and processing the latest map element according to the target processing method to obtain a processed latest map.
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公开(公告)号：US20230032324A1
公开(公告)日：2023-02-02
申请号：US17966127
申请日：2022-10-14
Inventor： Fan WANG , Hao TIAN , Haoyi XIONG , Hua WU , Jingzhou HE , Haifeng WANG
IPC: G06N20/00
Abstract: A method for training a decision-making model parameter, a decision determination method, an electronic device, and a non-transitory computer-readable storage medium are provided. In the method, a perturbation parameter is generated according to a meta-parameter, and first observation information of a primary training environment is acquired based on the perturbation parameter. According to the first observation information, an evaluation parameter of the perturbation parameter is determined. According to the perturbation parameter and the evaluation parameter thereof, an updated meta-parameter is generated. The updated meta-parameter is determined as a target meta-parameter, when it is determined, according to the meta-parameter and the updated meta-parameter, that a condition for stopping primary training is met. According to the target meta-parameter, a target memory parameter corresponding to a secondary training task is determined, where the target memory parameter and the target meta-parameter are used to make a decision corresponding to a prediction task.
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公开(公告)号：US20220391774A1
公开(公告)日：2022-12-08
申请号：US17887951
申请日：2022-08-15
Inventor： Feng XING , Xiang LAN , Liling NIU , Xiandong LIU , Yanjun MA , Dianhai YU , Haifeng WANG
Abstract: A method and apparatus for generating an operator are provided. The method includes: constructing a group of basic application programming interfaces for providing one of the following basic functions: an access function, a storage function, and a computing function; constructing a kernel application programming interface for invoking the basic application programming interfaces to implement an operator logic; and generating a target kernel operator based on the group of basic application programming interfaces and the kernel application programming interface.
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公开(公告)号：US20220391602A1
公开(公告)日：2022-12-08
申请号：US17820765
申请日：2022-08-18
Inventor： Haifeng WANG , Zhanyi LIU , Zhongjun HE , Hua WU , Zhi LI , Xing WAN , Jingxuan ZHAO , Ruiqing ZHANG , Chuanqiang ZHANG , Fengtao HUANG , Hanbing SONG , Wei DI , Shuangshuang CUI , Yongzheng XIN
Abstract: A display method, an electronic device, and a storage medium, which relate to a field of natural language processing and a field of display. The display method includes: acquiring a content to be displayed; extracting a target term from the content using a term extraction rule; acquiring an annotation information for at least one target term, responsive to an extraction of the at least one target term; and displaying the annotation information for the at least one target term and the content.
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