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Patent Agency Ranking
公开(公告)号：US12277401B2
公开(公告)日：2025-04-15
申请号：US17502108
申请日：2021-10-15
Inventor： Guocheng Niu , Wei Li , Can Gao , Xinyan Xiao , Hua Wu
IPC: G06F18/25 , G06F40/205 , G06F40/47 , G06F40/58 , G06N3/02
Abstract: The present disclosure discloses a method and apparatus for acquiring a pre-trained model, and relates to natural language processing and deep learning technologies in the field of artificial intelligence technologies. An implementation includes: acquiring training data, the training data including a single-modal language material and a multi-modal language material, and the multi-modal language material including a language material pair formed by a first-modal language material and a second-modal language material; and performing a multi-task training operation on a pre-trained model using the training data, the multi-task including at least one cross-modal contrastive learning task and at least one single-modal learning task; the pre-trained language model obtained in the present disclosure may learn from different forms of language materials, i.e., the single-modal language material and the multi-modal language material, such that the pre-trained language model may effectively process information in various modals.
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公开(公告)号：US12093297B2
公开(公告)日：2024-09-17
申请号：US17577561
申请日：2022-01-18
Inventor： Wenhao Wu , Wei Li , Xinyan Xiao , Jiachen Liu
CPC classification number: G06F16/345 , G06F40/51 , G06F40/56
Abstract: The present disclosure provides a summary generation model training method and apparatus, a device and a storage medium, and relates to the field of computer technologies, and in particular, to the field of artificial intelligence such as natural language processing and deep learning. The summary generation model training method includes: acquiring a document representation corresponding to a document sample; constructing, based on the document representation, a summary representation corresponding to the document representation, the summary representation including a positive summary representation and a negative summary representation; and constructing a total contrastive loss function based on the document representation, the positive summary representation and the negative summary representation, and training a summary generation model based on the total contrastive loss function. The present disclosure may improve accuracy of the summary generation model.
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3.发明申请公开(公告)号：US20220327809A1
公开(公告)日：2022-10-13
申请号：US17809133
申请日：2022-06-27
Inventor： Wei Li , Can Gao , Guocheng Niu , Xinyan Xiao , Hao Liu , Jiachen Liu , Hua Wu , Haifeng Wang
IPC: G06V10/778 , G06V10/774 , G06V10/26 , G06F40/284
Abstract: A method for training a model based on multi-modal data joint learning, includes: obtaining multi-modal data; in which the multi-modal data include at least one type of single-modal data and at least one type of Pair multi-modal data; inputting the single-modal data and the Pair multi-modal data into a decoupling attention Transformer network model to generate respectively Token semantic representation features and cross-modal semantic representation features; and training the decoupling attention Transformer network model based on the Token semantic representation features and the cross-modal semantic representation features.
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公开(公告)号：US20230114673A1
公开(公告)日：2023-04-13
申请号：US18059645
申请日：2022-11-29
Inventor： Wei Li , Xinyan Xiao , Jiachen Liu
Abstract: A method for recognizing a token is performed by an electronic device. The method includes: obtaining first modal data and second modal data; determining a first token of the first modal data and a second token of the second modal data; determining an associated token between the first token and the second token; and recognizing a target shared token between the first modal data and the second modal data based on the first token, the second token and the associated token.
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公开(公告)号：US20230025458A1
公开(公告)日：2023-01-26
申请号：US17932357
申请日：2022-09-15
Inventor： Wei Li , Hailu Jia , Xi Chen , Fangsheng Jiang , Guangdi Shan
Abstract: A positioning method and an on-board device. The method includes: acquiring positioning data of a vehicle from a satellite and positioning correction data from a base station; acquiring target positioning data of the vehicle by correcting the positioning data based on the positioning correction data; and sending the target positioning data to a terminal device to enable the terminal device to position the vehicle according to the target positioning data.
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