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公开(公告)号：US20240338862A1
公开(公告)日：2024-10-10
申请号：US18749461
申请日：2024-06-20
Inventor： Jiachen LIU , Xinyan XIAO , Hua WU , Guohao LI , Wei LI , Hong ZHU , Qiaoqiao SHE , Yajuan LV
Abstract: A method is provided that includes: obtaining current dialogue data; determining a requirement type of the user in the current round of dialogue based on the current dialogue data; in response to the requirement type being an image processing requirement, determining an action sequence for implementing the image processing requirement; executing the action sequence to generate a target image; and generating response data corresponding to the user input data based on the target image.
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公开(公告)号：US20240362493A1
公开(公告)日：2024-10-31
申请号：US18770122
申请日：2024-07-11
Inventor： Yixuan SHI , Wei LI , Jiachen LIU , Xinyan XIAO
IPC: G06N3/092 , G06N3/045 , G06N3/0475 , G06N3/09 , G06T11/00
CPC classification number: G06N3/092 , G06N3/045 , G06N3/0475 , G06N3/09 , G06T11/00
Abstract: A method is provided that includes: obtaining a first Text-to-Image model and a pre-trained reward model, wherein the first Text-to-Image model is used to generate a corresponding image based on input text, and the pre-trained reward model is used to score a data pair composed of the input text and the corresponding generated image; and adjusting the parameters of the first Text-to-Image model based on the pre-trained reward model and a reinforcement learning policy to obtain a second Text-to-Image model.
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公开(公告)号：US20220292269A1
公开(公告)日：2022-09-15
申请号：US17502108
申请日：2021-10-15
Inventor： Guocheng NIU , Wei LI , Can GAO , Xinyan XIAO , Hua WU
IPC: G06F40/58 , G06F40/47 , G06F40/205
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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Patent Agency Ranking
公开(公告)号：US20250078369A1
公开(公告)日：2025-03-06
申请号：US18953942
申请日：2024-11-20
Inventor： Guohao LI , Jiachen LIU , Xinyan XIAO
IPC: G06T11/60 , G06F40/174 , G06F40/186 , G06F40/40 , G06T5/60 , G06T5/70
Abstract: A method is provided that includes: obtaining an editing instruction input by a user in a current round of a dialogue and history dialogue information in at least one history round of the dialogue, wherein the history dialogue information comprises a history dialogue text and at least one history image; determining a source image to be edited from the at least one history image based on the editing instruction and the history dialogue information; and editing the source image to generate a target image based on the editing instruction.
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公开(公告)号：US20230214423A1
公开(公告)日：2023-07-06
申请号：US18174481
申请日：2023-02-24
Inventor： Haifeng WANG , Hao TIAN , Xinyan XIAO , Xing LI , Tian WU
IPC: G06F16/783 , G06F16/73 , G06N3/0895 , G06F40/30 , G06F40/40 , G06F40/295 , G10L15/22 , G10L15/18 , G10L15/16 , G10L25/57
CPC classification number: G06F16/7844 , G06F16/73 , G06F40/30 , G06F40/40 , G06F40/295 , G06N3/0895 , G10L15/16 , G10L15/22 , G10L15/1815 , G10L25/57
Abstract: A video generation method is provided. The video generation method includes: obtaining global semantic information and local semantic information of a text, where the local semantic information corresponds to a text fragment in the text, searching, based on the global semantic information, a database to obtain at least one first data corresponding to the global semantic information; searching, based on the local semantic information, the database to obtain at least one second data corresponding to the local semantic information; obtaining, based on the at least one first data and the at least one second data, a candidate data set; matching, based on a relevancy between each of at least one text fragment and corresponding candidate data in the candidate data set, target data for the at least one text fragment; and generating, based on the target data matched with each of the at least one text fragment, a video.
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6.发明申请公开(公告)号：US20230004717A1
公开(公告)日：2023-01-05
申请号：US17572068
申请日：2022-01-10
Inventor： Lijie WANG , Shuai ZHANG , Xinyan XIAO , Yue CHANG , Tingting LI
IPC: G06F40/289 , G06N20/00
Abstract: The present disclosure provides a method and apparatus for acquiring a pre-trained model, an electronic device and a storage medium, and relates to the field of artificial intelligence, such as the natural language processing field, the deep learning field, or the like. The method may include: adding, in a process of training a pre-trained model using training sentences, a learning objective corresponding to syntactic information for a self-attention module in the pre-trained model; and training the pre-trained model according to the defined learning objective. The solution of the present disclosure may improve a performance of the pre-trained model, and reduce consumption of computing resources, or the like.
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公开(公告)号：US20230004589A1
公开(公告)日：2023-01-05
申请号：US17577561
申请日：2022-01-18
Inventor： Wenhao WU , Wei LI , Xinyan XIAO , Jiachen LIU
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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公开(公告)号：US20220179889A1
公开(公告)日：2022-06-09
申请号：US17652314
申请日：2022-02-24
Inventor： Ao ZHANG , Lijie WANG , Xinyan XIAO , Tingting LI
IPC: G06F16/332 , G06F16/33
Abstract: The disclosure provides a method for generating a query statement. The method includes: determining a first vector representation based on known nodes in a first syntax tree corresponding to a query statement to be generated; determining a target generation strategy corresponding to a target node to be generated based on the first vector representation and a preset copy reference matrix; generating the target node based on the first vector representation or a second vector representation by performing the target generation strategy, in which the second vector representation is a vector representation corresponding to an adjacent query statement prior to the query statement to be generated; and generating the query statement based on the known nodes and a terminator in response to the target node being the terminator.
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