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公开(公告)号：US20250094877A1
公开(公告)日：2025-03-20
申请号：US18969719
申请日：2024-12-05
Inventor： Fan WANG , Hua WU , Yingzhan LIN , Zengfeng ZENG , Yufeng HU , Jianhui DING , Haifeng WANG
IPC: G06N20/00
Abstract: A large model-based method of generating a text, a method of training a text generation model, a device, and a medium are provided, which relate to a field of artificial intelligence technology, specifically to fields of deep learning, natural language processing and large model technologies. The large model-based method of generating a text includes: acquiring a memory state for a text to be processed, where the memory state is generated based on a previous text of the text to be processed; determining an embedding feature of the text to be processed as an initial hidden state, and processing the memory state and the initial hidden state by using a first attention mechanism to obtain an updated hidden state; and generating a subsequent text for the text to be processed based on the updated hidden state.
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公开(公告)号：US20250094713A1
公开(公告)日：2025-03-20
申请号：US18967529
申请日：2024-12-03
Inventor： Shuohuan WANG , Yekun CHAI , Siyu DING , Junyuan SHANG , Zhenyu ZHANG , Yu SUN , Hao TIAN , Hua WU , Haifeng WANG
IPC: G06F40/284 , G06F16/3329
Abstract: A multimodal data generation method is provided. The method includes: inputting a query data sequence into a multimodal model, to obtain a plurality of tokens in a response data sequence, where a current token is generated through the following operations: inputting the query data sequence and a current response data sequence into the multimodal model, so that the multimodal model generates the current token based on the query data sequence and the current response data sequence, in response to determining that the current token belongs to a first data modality; or inputting the query data sequence and a current response data sequence into the multimodal model, so that the multimodal model denoises an initial token sequence based on the query data sequence and the current response data sequence, to generate a result token sequence, in response to determining that the current token belongs to a second data modality.
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公开(公告)号：US20250004771A1
公开(公告)日：2025-01-02
申请号：US18755148
申请日：2024-06-26
Inventor： Haifeng WANG , Hua WU , Dai DAI , Jing LIU , Hongyu LI , Gangqiang HU
Abstract: A method, apparatus, device, and medium for generating instruction data is provided. The method includes: obtaining a natural language-based reference instruction to direct a large model to generate response data meeting multiple first requirements; obtaining a structured disassembly result of the reference instruction to derive several reference slots and slot values corresponding to these requirements; determining multiple sample slots and sample slot values based on the reference slots, slot values, and a predetermined rule; and generating a natural language-based sample instruction from these sample slots and values, which directs the large model to generate response data that fulfills multiple second requirements.
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公开(公告)号：US20240378077A1
公开(公告)日：2024-11-14
申请号：US18782617
申请日：2024-07-24
Inventor： Guoxia WANG , Jinle ZENG , Xiyuan XIAO , Jiabin YANG , Dianhai YU , Haifeng WANG
Abstract: A method of executing a task for a large language model, a device, and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of deep learning, large language model, natural language processing and computer vision technologies. The method includes: determining, by using a determination unit, a target attention task from a plurality of attention tasks to be processed, based on a sparse representation corresponding to a feature to be processed, where the target attention task is a task corresponding to a non-fully masked region of the feature, the sparse representation represents a mask position of the feature, and the mask position represents mask endpoint positions in at least two non-intersecting intervals in a mask matrix corresponding to the feature; and executing the target attention task by using a computing unit, so as to obtain an attention feature.
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5.发明公开公开(公告)号：US20240177469A1
公开(公告)日：2024-05-30
申请号：US17793999
申请日：2021-11-17
Inventor： Miao FAN , Jizhou HUANG , Haifeng WANG
IPC: G06V10/82 , G06V10/771 , G06V10/80
CPC classification number: G06V10/82 , G06V10/771 , G06V10/80
Abstract: A method and apparatus for encoding a geographic location region as well as a method and apparatus for establishing an encoding model, which relate to big data and deep learning technologies in the field of artificial intelligence technologies are disclosed. An implementation includes: determining a to-be-encoded geographic location region; acquiring at least one kind of geographic function information and at least one kind of surface-feature distribution information of the geographic location region; and inputting the acquired geographic function information and the acquired surface-feature distribution information into an encoding model, the encoding model performing embedding on the geographic function information and the surface-feature distribution information, and fusing vector representations obtained by the embedding to obtain an encoding result of the geographic location region.
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Patent Agency Ranking
公开(公告)号：US20230419610A1
公开(公告)日：2023-12-28
申请号：US18185359
申请日：2023-03-16
Inventor： Xing LIU , Ruizhi CHEN , Yan ZHANG , Chen ZHAO , Hao SUN , Jingtuo LIU , Errui DING , Tian WU , Haifeng WANG
CPC classification number: G06T17/20 , G06T5/50 , G06V10/26 , G06V10/60 , G06T2207/10028 , G06T2207/20221
Abstract: An image rendering method includes the steps below. A model of an environmental object is rendered to obtain an image of the environmental object in a target perspective. An image of a target object in the target perspective and a model of the target object are determined according to a neural radiance field of the target object. The image of the target object is fused and rendered into the image of the environmental object according to the model of the target object.
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7.发明公开公开(公告)号：US20230289402A1
公开(公告)日：2023-09-14
申请号：US18055393
申请日：2022-11-14
Inventor： Jian WANG , Xiangbo SU , Qiman WU , Zhigang WANG , Hao SUN , Errui DING , Jingdong WANG , Tian WU , Haifeng WANG
IPC: G06K9/62
CPC classification number: G06K9/62 , G06K9/6288
Abstract: Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.
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公开(公告)号：US20230090590A1
公开(公告)日：2023-03-23
申请号：US17738651
申请日：2022-05-06
Inventor： Xiaoyin FU , Zhijie CHEN , Mingxin LIANG , Mingshun YANG , Lei JIA , Haifeng WANG
IPC: G10L15/02 , G10L15/26 , G10L15/187 , G06F16/683
Abstract: The present disclosure provides speech recognition and codec methods and apparatuses, an electronic device and a storage medium, and relates to the field of artificial intelligence such as intelligent speech, deep learning and natural language processing. The speech recognition method may include: acquiring an audio feature of to-be-recognized speech; encoding the audio feature to obtain an encoding feature; truncating the encoding feature to obtain continuous N feature fragments, N being a positive integer greater than one; and acquiring, for any one of the feature segments, corresponding historical feature abstraction information, encoding the feature segment in combination with the historical feature abstraction information, and decoding an encoding result to obtain a recognition result corresponding to the feature segment, wherein the historical feature abstraction information is information obtained by feature abstraction of recognized historical feature fragments.
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公开(公告)号：US20230008897A1
公开(公告)日：2023-01-12
申请号：US17932598
申请日：2022-09-15
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/735
Abstract: An information search method includes: obtaining search words at least including a question to be searched and obtaining an initial text vector representation of the search words; obtaining a video corresponding to the search words, and obtaining multi-modality vector representations of the video; starting from the initial text vector representation, performing N rounds of interaction between the video and the search words based on the multi-modality vector representations and a text vector representation of the search words of a current round, to generate a target fusion vector representation, where N is an integer greater than or equal to 1; and obtaining target video frames matching the question to be searched by annotating the video based on the target fusion vector representation.
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公开(公告)号：US20220035614A1
公开(公告)日：2022-02-03
申请号：US17500779
申请日：2021-10-13
Inventor： Liujie ZHANG , Xiang LAN , Huihuang ZHENG , Hongyu LIU , Wei ZHOU , Yanjun MA , Dianhai YU , Haifeng WANG
Abstract: The present disclosure discloses a method, an apparatus and an electronic device for deploying an operator in a deep learning framework and relates to the field of artificial intelligence technology such as deep learning. And the solution is: acquiring a source file of the operator; compiling the source file of the operator to form a dynamic link library of the operator; generating an interface file transferred from the dynamic link library of the operator; generating an installable library file according to the dynamic link library and the interface file; installing the installable library file to a target programming language library.
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