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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:US20210191962A1
公开(公告)日:2021-06-24
申请号:US17088053
申请日:2020-11-03
IPC: G06F16/33 , G06F40/40 , G06K9/00 , G06F16/332 , G06F16/338 , G06N3/08
Abstract: Provided are a question answering method and language model training method, apparatus, device, and storage media, including: acquiring at least one candidate table matching a question to be queried, each candidate table includes a candidate answer corresponding to the question; processing the at least one candidate table to obtain at least one table text, the table text includes textual content of respective fields in the candidate table; inputting the question and each table text into a preset language model respectively to obtain a degree of matching between the question and each candidate table; and outputting a reply table according to the degree of matching of each candidate table, the reply table is a candidate table out of the at least one candidate table whose degree of matching with the question is greater than a preset value or a candidate table that corresponds to a maximum degree of matching.
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公开(公告)号:US20240419484A1
公开(公告)日:2024-12-19
申请号:US18817035
申请日:2024-08-27
IPC: G06F9/48
Abstract: A method for processing information is provided. The method includes obtaining input information to be processed. The method further includes determining execution information associated with processing of the input information. The execution information includes at least one of memory information to be retrieved or tool information to be invoked. The method further includes obtaining, by using the execution information, at least one piece of processing result information corresponding to the processing of the input information. The method further includes the at least one piece of processing result information to generate output information for feedback.
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公开(公告)号:US20230147798A1
公开(公告)日:2023-05-11
申请号:US18052143
申请日:2022-11-02
Inventor: Haifeng WANG , Hao TIAN , Jing LIU , Hua WU , Tian WU , Yu SUN , Qiaoqiao SHE
CPC classification number: G06F16/3347 , G06F40/30
Abstract: A method is provided. The method includes converting a search request of a user into a first request semantic vector. The method further includes searching a search resource database for at least one first data semantic vector matched with the first request semantic vector, wherein the search resource database is constructed as a semantic vector space in which different types of data are converted into corresponding data semantic vectors, and the different types of data include at least texts, pictures and videos. The method further includes generating, based on the at least one first data semantic vector, a search result.
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公开(公告)号:US20230061398A1
公开(公告)日:2023-03-02
申请号:US17984034
申请日:2022-11-09
Inventor: Shangwen LYU , Hongyu LI , Jing LIU , Hua WU , Haifeng WANG
IPC: G06V30/19 , G06V30/412 , G06V30/194 , G06F40/205
Abstract: A method for training a document reading comprehension model includes: acquiring a question sample and a rich-text document sample, in which the rich-text document sample includes a real answer of the question sample; acquiring text information and layout information of the rich-text document sample by performing OCR processing on image information of the rich-text document sample; acquiring a predicted answer of the question sample by inputting the text information, the layout information and the image information of the rich-text document sample into a preset reading comprehension model; and training the reading comprehension model based on the real answer and the predicted answer. The method may enhance comprehension ability of the reading comprehension model to the long rich-text document, and save labor cost.
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公开(公告)号:US20250094460A1
公开(公告)日:2025-03-20
申请号:US18969597
申请日:2024-12-05
Inventor: Haifeng WANG , Hua WU , Hao TIAN , Jing LIU , Ruiqing ZHANG , Yan CHEN , Yu RAN
IPC: G06F16/3329 , G06F16/3332 , G06F16/334
Abstract: A query answering method, an electronic device, a storage medium, and an intelligent agent are provided, which relate to a field of artificial intelligence technology, and in particular to fields of large model, intelligent search and information processing technology. The method includes: inputting, in response to a retrieval content set retrieved based on a query, the query, the retrieval content set and prompt information for answer generation into the large model, so that the large model performs operations of: processing, based on a current task in the prompt information and the query, a current text corresponding to the retrieval content set to obtain a processed text, where the current task is determined based on a task execution order in the prompt information; and obtaining, in a case of determining that the processed text meets a preset condition, an answer to the query based on the processed text.
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