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公开(公告)号：US12283085B2
公开(公告)日：2025-04-22
申请号：US17902323
申请日：2022-09-02
Inventor： Siqi Xu , Ke Sun , Jian Gong , Xu Pan , Zhiqun Xia , Zhe Yang , Zecheng Zhuo
IPC: G06V10/762 , G06F16/28 , G06V10/74 , G06V10/764
Abstract: Provided is a data labeling method based on artificial intelligence, an apparatus, and a storage medium relating to the field of artificial intelligence, particularly data labeling, image recognition, and natural language processing. The method includes: determining a plurality of samples involved in clustering; performing a plurality of following operations circularly to realize iterative processing, until a convergence condition is satisfied or a quantity of iterations reaches a number threshold, comprising: pre-clustering the plurality of samples according to a vector representation of the respective samples to obtain a plurality of class clusters, each class cluster containing at least one sample; receiving labeling information for the respective class clusters and re-determining the plurality of samples according to the labeling information; and determining a clustering result according to the labeling information for the respective class clusters.
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302.发明申请公开(公告)号：US20250124679A1
公开(公告)日：2025-04-17
申请号：US18748082
申请日：2024-06-19
Inventor： Lei WANG , Xiaodong ZHANG , Shiyan LI
Abstract: The present disclosure provides method and apparatus for transferring facial expression of digital human, electronic device, and storage medium, which relates to the fields of augmented reality technologies, virtual reality technologies, computer vision technologies, deep learning technologies, or the like, and can be applied to scenarios, such as metaverse, a virtual digital human, or the like, An implementation includes: screening an identification of a target reference model matched with an object model from a preset reference model library; the reference model library including a plurality of reference models; acquiring an expression library of the target reference model based on the identification of the target reference model; and transferring a last frame of an expression in the expression library of the target reference model into the object model to obtain a last frame of an expression of the object model.
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公开(公告)号：US12277398B2
公开(公告)日：2025-04-15
申请号：US17694034
申请日：2022-03-14
Inventor： Jian Gong , Yu Sun , Hao Tian , Hua Wu , Haifeng Wang , Qiaoqiao She
IPC: G06F40/40 , G06F40/205 , G06F40/284
Abstract: A model training method, a model training platform, an electronic device and a storage medium are provided, which can be used in the field of artificial intelligence, particularly the fields of natural language processing and deep learning. The model training method includes: receiving an input; determining, based on the input, a user-oriented prefabricated function; determining, based on the input, a model training function; determining, based on the input, a pre-trained model; determining, based on the input, a network structure associated with the pre-trained model so as to support use of the pre-trained model; training, based on the input, the model by using the prefabricated function, the model training function, and the pre-trained model; and providing an output associated with a trained model.
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公开(公告)号：US12277387B2
公开(公告)日：2025-04-15
申请号：US18056197
申请日：2022-11-16
Inventor： Ruiqing Zhang , Zhongjun He , Zhi Li , Hua Wu
IPC: G06F40/232 , G06F40/279 , G06F40/53
Abstract: A text processing method is provided. The method includes: a first probability value of each candidate character of a plurality of candidate characters corresponding to a target position is determined based on character feature information corresponding to the target position in a text fragment to be processed, wherein the character feature information is determined based on a context at the target position in the text fragment to be processed; a second probability value of each candidate character of the plurality of candidate characters is determined based on a character string including the candidate character and at least one character in at least one position in the text fragment to be processed adjacent to the target position; and a correction character at the target position is determined based on the first probability value and the second probability value of each candidate character of the plurality of candidate characters.
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305.发明申请公开(公告)号：US20250117668A1
公开(公告)日：2025-04-10
申请号：US18987988
申请日：2024-12-19
Inventor： Xinran He , Xianwei Xue , Bolei He , Kunbin Chen , Jinchang Luo , Ruigao Li
IPC: G06N3/096 , G06N3/0475
Abstract: A method for model training based on a large model includes: determining a first large model as a teacher model of a language model, and performing distillation learning on the language model based on the first large model; inputting a first prompt text into the language model, and obtaining a plurality of first response texts for the first prompt text output by the language model; determining a reference response text for the first prompt text from the plurality of first response texts; and training the language model based on the reference response text for the first prompt text.
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Patent Agency Ranking
公开(公告)号：US12270672B2
公开(公告)日：2025-04-08
申请号：US17712557
申请日：2022-04-04
Inventor： Tingting Zhai , Peng Yang , Hongfei Zhu
IPC: G01C21/36
Abstract: The present disclosure provides a method for generating navigation information, an apparatus for generating navigation information, a device, a medium, and a product. The present disclosure relates to the technical field of computers, and specifically relates to the technical field of artificial intelligence, and the present disclosure may be applied to a map navigation scenario. A specific implementation includes: acquiring intersection feature information; determining a set of a complex intersection based on the intersection feature information; determining intersection type information corresponding to the complex intersection in the set of the complex intersection; and generating navigation information corresponding to the complex intersection in the set of the complex intersection based on the intersection type information.
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公开(公告)号：US20250103825A1
公开(公告)日：2025-03-27
申请号：US18974450
申请日：2024-12-09
Inventor： Xinchao Xu , Wenquan Wu
IPC: G06F40/35
Abstract: A method for generating a dialogue includes acquiring a current first question statement and historical dialogue information associated with the first question statement; acquiring, from a knowledge base, a first knowledge item associated with the first question statement and a second knowledge item having a question-answer relationship with the first knowledge item; obtaining a first reply statement output by a generative model by inputting the first question statement, the first knowledge item, and the historical dialogue information into the generative model; evaluating the first reply statement based on the first question statement, the first knowledge item, and the second knowledge item; and outputting the first reply statement in response to the first reply statement passing evaluation.
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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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310.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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