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公开(公告)号：US12260492B2
公开(公告)日：2025-03-25
申请号：US18099602
申请日：2023-01-20
Inventor： Di Wang , Ruizhi Chen , Chen Zhao , Jingtuo Liu , Errui Ding , Tian Wu , Haifeng Wang
Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.
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公开(公告)号：US12260186B2
公开(公告)日：2025-03-25
申请号：US17992436
申请日：2022-11-22
Inventor： Zhe Hu , Jiachen Liu , Xinyan Xiao
Abstract: A method of generating a text, a method of training a text generation model, an electronic device, and a storage medium, which relate to a field of a computer technology, in particular to fields of deep learning and natural language processing technologies. A specific implementation solution includes: determining a reference feature representation of a target semantic information; determining, based on the reference feature representation and at least one predetermined logical character, at least one sentence latent representation respectively corresponding to the at least one predetermined logical character; and generating a target text content based on the at least one sentence latent representation.
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313.发明申请公开(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：US20250094806A1
公开(公告)日：2025-03-20
申请号：US18967167
申请日：2024-12-03
Inventor： Junyuan Shang , Yilong Chen , Zhenyu Zhang , Shuohuan Wang , Yu Sun , Hua Wu
IPC: G06N3/082 , G06N3/0475
Abstract: Provided is a large language model training method, an electronic device and a storage medium, relating to the field of artificial intelligence technologies, and in particular, to the fields of deep learning, natural language processing and large model. The method includes: performing dimension reduction parameter fusion on a two-dimensional parameter matrix on each channel in each network layer in a first large language model, respectively, to obtain a second large language model; performing layer reduction parameter fusion on network layers in the second large language model based on a three-dimensional parameter matrix of each network layer in the second large language model to obtain a third large language model; and training the third large language model to obtain a target large language model under the condition that the target loss function determined based on the first and third large language models meets a preset first function condition.
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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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Patent Agency Ranking
公开(公告)号：US20250094139A1
公开(公告)日：2025-03-20
申请号：US18965152
申请日：2024-12-02
Inventor： Dianhai YU , Wei ZHOU , Xiang GAO , Tiezhu GAO
Abstract: A method of generating a code based on a large model, an electronic device and a storage medium are provided, which relate to the field of artificial intelligence technology, in particular to the fields of deep learning technology and large model technology. The method includes: acquiring a first descriptive text input by a user, where the first descriptive text is configured to characterize a code requirement; searching for a positive code and a negative code matching the first descriptive text, where each of the positive code and the negative code is determined based on a preference operation of the user for a historical code output by the large model; generating a second descriptive text according to the first descriptive text, the positive code, and the negative code; and inputting the second descriptive text into the large model to output a target code matching the code requirement.
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公开(公告)号：US20250078305A1
公开(公告)日：2025-03-06
申请号：US18043705
申请日：2022-06-20
Inventor： Lei WANG , Ying WANG , Xiaoting ZANG
IPC: G06T7/70
Abstract: The present disclosure provides a data marking method, apparatus, system, device, and storage medium, and relates to the technical field of data processing, and in particular to fields such as artificial intelligence, big data, and deep learning. The specific implementation solution is as follows: acquiring multiple pictures whose contents are continuous, wherein the multiple pictures contain at least one same object; for each object, determining a position offset of the object by using position information of the object in two adjacent pictures, wherein the two adjacent pictures include a first previous picture and a second previous picture, the second previous picture is a picture before and adjacent to a picture to be marked in time sequence; the first previous picture is a picture before and adjacent to the second previous picture in time sequence; determining estimated position information of the object in the picture to be marked based on the position information of the second previous picture and the position offset; marking the object in the picture to be marked based on the estimated position information. The present disclosure can speed up the marking of the same object in multiple pictures.
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公开(公告)号：US20250054572A1
公开(公告)日：2025-02-13
申请号：US18930048
申请日：2024-10-29
Inventor： Jie Gao , Jing Hu , Xiaomin Fang , Xiaonan Zhang
IPC: G16B15/30
Abstract: A method for protein docking includes docking a first protein and a second protein according to at least two molecular docking methods to generate a complex conformation in each round of iteration; recognizing that an iteration end condition is not satisfied, continuing a next round of iteration until the iteration end condition is satisfied, and obtaining a final complex conformation.
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公开(公告)号：US12223271B2
公开(公告)日：2025-02-11
申请号：US17874394
申请日：2022-07-27
Inventor： Zeyu Chen , Haifeng Wang , Tian Wu , Dianhai Yu , Yanjun Ma , Xiaoguang Hu
IPC: G06F40/10 , G06F40/284 , G06F40/47
Abstract: Provided are a text processing method, a device and a storage medium, relating to a field of computer technology, and especially to a field of artificial intelligence, such as natural language processing and deep learning. The specific implementation scheme includes: performing text processing on first text, by using a text processing acceleration operator; and processing, in parallel and faster, content after the text processing, by using the text processing acceleration operator. Text processing and parallel acceleration are carried out by the text processing acceleration operator, which can improve the speed of text processing.
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公开(公告)号：US12210507B2
公开(公告)日：2025-01-28
申请号：US17907465
申请日：2020-09-24
Inventor： Wei Qiang , Wengen Li , Jingying Qu , Anzhan Zhang , Cheng Liu , Li Sun
Abstract: A method for monitoring a running state of a distributed system, an electronic device, and a storage medium are provided. The method comprises: acquiring a first calling key-value pair sent by a first component in a distributed system (101); and determining the current running state of the first component according to a first keyword value, and historical calling data corresponding to a first key code value in a preset database (102).
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