Patents by Inventor Jinchang Luo

Jinchang Luo has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250117668
    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.
    Type: Application
    Filed: December 19, 2024
    Publication date: April 10, 2025
    Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
    Inventors: Xinran He, Xianwei Xue, Bolei He, Kunbin Chen, Jinchang Luo, Ruigao Li
  • Publication number: 20250117714
    Abstract: A method for generating a text training sample based on a large model includes: obtaining at least two query clusters by clustering at least two queries; obtaining a first query from each query cluster; generating at least two second queries under a set theme through a first large model by taking the first query as an example; and generating a first text training sample for fine-tuning a second large model based on the second query.
    Type: Application
    Filed: December 19, 2024
    Publication date: April 10, 2025
    Applicant: BAIDU INTERNATIONAL TECHNOLOGY (SHENZHEN) CO., LTD.
    Inventors: Jinchang Luo, Bolei He, Kunbin Chen, Wei He
  • Publication number: 20250013676
    Abstract: A computer-implemented method for information processing based on a large language model is provided. The method includes obtaining query information provided by a user. The method further includes determining memory information related to the query information. The method further includes determining, based on the query information and the memory information, a tool for processing the query information. The method further includes invoking the tool to obtain auxiliary information. The method further includes generating, based on the query information and the auxiliary information, a result of processing the query information.
    Type: Application
    Filed: September 19, 2024
    Publication date: January 9, 2025
    Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
    Inventors: Jinchang LUO, Bolei HE, Kunbin CHEN, Wei HE
  • Publication number: 20250013876
    Abstract: An apparatus for training a large language model includes: at least one sample text instruction is input into a target large language model to obtain at least one standard response text, and the at least one sample text instruction is input into a large language model to be trained to obtain at least one predicted response text. A first sample response text is determined from the at least one standard response text according to the score difference between a first quality score of a standard response text and a second quality score of a predicted response text. A first target training sample is generated according to the first sample response text and a sample text instruction corresponding to the first sample response text, and a training dataset is constructed according to the first target training sample.
    Type: Application
    Filed: September 19, 2024
    Publication date: January 9, 2025
    Inventors: Xianwei XUE, Qiutong PAN, Jinchang LUO, Bolei HE, Wei HE
  • Publication number: 20230085599
    Abstract: The disclosure provides a method for training a tag recommendation model. The method includes: collecting training materials that comprise interest tags in response to receiving an instruction for collecting training materials; obtaining training semantic vectors that comprise the interest tags by representing features of the training materials using a semantic enhanced representation frame; obtaining training encoding vectors by aggregating social networks into the training semantic vectors; and obtaining a tag recommendation model by training a double-layer neural network structure using the training encoding vectors as inputs and the interest tags as outputs. Therefore, the interest tags obtained in the disclosure are more accurate.
    Type: Application
    Filed: November 21, 2022
    Publication date: March 16, 2023
    Inventors: Jinchang LUO, Haiwei WANG, Junzhao BU, Kunbin CHEN, Wei HE
  • Publication number: 20220406034
    Abstract: A method for extracting information, includes: obtaining an information stream comprising text and an image; generating, according to the text, embedded representations of textual entity mentions and a textual similarity matrix of the textual entity mentions and candidate textual entities; generating, according to the image, embedded representations of image entity mentions and an image similarity matrix of the image entity mentions and candidate image entities; and determining, based on an optimal transport, target textual entities of the textual entity mentions and target image entities of the image entity mentions according to the embedded representations of the textual entity mentions, the embedded representations of the image entity mentions, the textual similarity matrix and the image similarity matrix.
    Type: Application
    Filed: August 29, 2022
    Publication date: December 22, 2022
    Inventors: Jingru GAN, Haiwei WANG, Jinchang LUO, Kunbin CHEN, Wei HE, Shuhui WANG
  • Publication number: 20220358292
    Abstract: The disclosure provides a method for recognizing an entity, an electronic device and a storage medium. The method includes: obtaining message data to be processed; obtaining entity mention information by processing the message data to be processed according to a multi-pattern matching method; determining one or more candidate entities associated with the entity mention information and entity description information corresponding to the one or more candidate entities; and determining a target entity mentioned in the entity mention information according to the message data to be processed and the entity description information.
    Type: Application
    Filed: July 20, 2022
    Publication date: November 10, 2022
    Applicant: Beijing Baidu Netcom Science Technology Co., LTD.
    Inventors: Fan Wang, Jinchang Luo, Jie Wang, Haiwei Wang, Kunbin Chen, Wei He