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    IMPLEMENTING TEXT GENERATION
    2.
    发明申请
    IMPLEMENTING TEXT GENERATION 有权

    公开(公告)号：US20210286934A1

    公开(公告)日：2021-09-16

    申请号：US17331526

    申请日：2021-05-26

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Jiachen LIU ,  Zhe HU ,  Xinyan XIAO ,  Hua WU

    IPC: G06F40/117 ,  G06F40/126 ,  G06N20/00

    Abstract: A method for implementing text generation, a device and a medium are provided. The method includes: determining a target task type of a target text generation task from multiple task types supported by a pre-trained general text generation model; determining, based on a requirement of the target text generation task for a target output text, a first target output text attribute for the target text generation task from multiple output text attributes supported by the general text generation model; and fine tuning the general text generation model based on a target training data set associated with the target text generation task to obtain a task-specific text generation model, by taking task indication information for the target task type and first attribute indication information for the first target output text attribute as at least part of an input of the general text generation model.

    METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM FOR TRAINING TEXT GENERATION MODEL
    4.
    发明申请
    METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM FOR TRAINING TEXT GENERATION MODEL 有权

    公开(公告)号：US20210374359A1

    公开(公告)日：2021-12-02

    申请号：US17133381

    申请日：2020-12-23

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Wei LI ,  Xinyan XIAO ,  Hua WU ,  Haifeng WANG

    IPC: G06F40/56 ,  G06F40/58

    Abstract: The disclosure may provide a method for obtaining a document layout, an electronic device, and a storage medium. The method may include: obtaining a plurality of pieces of first sample data; extracting structured information from each of the plurality of pieces of first sample data as target structured information corresponding to each of the plurality of pieces of first sample data; inputting the plurality of pieces of first sample data into an initial text generation model to generate predicted structured information corresponding to each of the plurality of pieces of first sample data; generating a first loss value based on a difference between the predicted structured information corresponding to each of the plurality of pieces of first sample data and the corresponding target structured information; and training a phrase generation ability of the initial text generation model based on the first loss value to generate the text generation model.

    METHOD AND APPARATUS FOR GENERATING DIALOGUE MODEL
    5.
    发明申请
    METHOD AND APPARATUS FOR GENERATING DIALOGUE MODEL 有权

    公开(公告)号：US20210200957A1

    公开(公告)日：2021-07-01

    申请号：US16895297

    申请日：2020-06-08

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Siqi BAO ,  Huang HE ,  Junkun CHEN ,  Fan WANG ,  Hua WU ,  Jingzhou HE

    IPC: G06F40/30

    Abstract: Embodiments of the present disclosure relate to a method and apparatus for generating a dialogue model. The method may include: acquiring a corpus sample set, a corpus sample including input information and target response information; classifying corpus samples in the corpus sample set, setting discrete hidden variables for the corpus samples based on a classification result to generate a training sample set, a training sample including the input information, the target response information, and a discrete hidden variable; and training a preset neural network using the training sample set to obtain the dialogue model, the dialogue model being used to represent a corresponding relationship between inputted input information and outputted target response information.

    END-TO-END MODEL TRAINING METHOD AND APPARATUS, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM
    6.
    发明申请
    END-TO-END MODEL TRAINING METHOD AND APPARATUS, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM 有权

    公开(公告)号：US20210192284A1

    公开(公告)日：2021-06-24

    申请号：US16901940

    申请日：2020-06-15

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Hao XIONG ,  Zhongjun HE ,  Zhi LI ,  Hua WU ,  Haifeng WANG

    IPC: G06K9/62 ,  G06F40/117

    Abstract: The present disclosure provides an end-to-end model training method and apparatus, which relates to a field of artificial intelligence technologies. The method includes: obtaining training data containing a plurality of training samples, in which the plurality of training samples include an original sequence, a target sequence and a corresponding tag list, the tag list includes importance tags in the target sequence and avoidance tags corresponding to the importance tags, and the avoidance tags are irrelevant tags corresponding to the importance tags; and adopting the training data to train a preset end-to-end model until a value of a preset optimization target function is smaller than a preset threshold.

    METHOD, APPARATUS, ELECTRONIC DEVICE AND STORAGE MEDIUM FOR PROCESSING A SEMANTIC REPRESENTATION MODEL
    7.
    发明申请
    METHOD, APPARATUS, ELECTRONIC DEVICE AND STORAGE MEDIUM FOR PROCESSING A SEMANTIC REPRESENTATION MODEL 有权

    公开(公告)号：US20210182498A1

    公开(公告)日：2021-06-17

    申请号：US16885358

    申请日：2020-05-28

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Yu SUN ,  Haifeng WANG ,  Shuohuan WANG ,  Yukun LI ,  Shikun FENG ,  Hao TIAN ,  Hua WU

    IPC: G06F40/30 ,  G06F40/40

    Abstract: The present disclosure provides a method, apparatus, electronic device and storage medium for processing a semantic representation model, and relates to the field of artificial intelligence technologies. A specific implementation solution is: collecting a training corpus set including a plurality of training corpuses; training the semantic representation model using the training corpus set based on at least one of lexicon, grammar and semantics. In the present disclosure, by building the unsupervised or weakly-supervised training task at three different levels, namely, lexicon, grammar and semantics, the semantic representation model is enabled to learn knowledge at levels of lexicon, grammar and semantics from massive data, enhance the capability of universal semantic representation and improve the processing effect of the NLP task.

    MULTI-LINGUAL MODEL TRAINING METHOD, APPARATUS, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM
    8.
    发明申请
    MULTI-LINGUAL MODEL TRAINING METHOD, APPARATUS, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM 有权

    公开(公告)号：US20220171941A1

    公开(公告)日：2022-06-02

    申请号：US17348104

    申请日：2021-06-15

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Xuan OUYANG ,  Shuohuan WANG ,  Chao PANG ,  Yu SUN ,  Hao TIAN ,  Hua WU ,  Haifeng WANG

    IPC: G06F40/30 ,  G06F40/58 ,  G06N20/00

    Abstract: The present disclosure provides a multi-lingual model training method, apparatus, electronic device and readable storage medium and relates to the technical field of deep learning and natural language processing. A technical solution of the present disclosure when training the multi-lingual model is: obtaining training corpuses comprising a plurality of bilingual corpuses and a plurality of monolingual corpuses; training a multi-lingual model with a first training task by using the plurality of bilingual corpuses; training the multi-lingual model with a second training task by using the plurality of monolingual corpuses; and completing the training of the multi-lingual model in a case of determining that loss functions of the first training task and second training task converge. In the present disclosure, the multi-lingual model can be enabled to achieve semantic interaction between different languages and improve the accuracy of the multi-lingual model in learning the semantic representations of the multi-lingual model.

    METHOD, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM FOR CREATING A LABEL MARKING MODEL
    10.
    发明申请
    METHOD, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM FOR CREATING A LABEL MARKING MODEL 有权

    公开(公告)号：US20210294975A1

    公开(公告)日：2021-09-23

    申请号：US17015411

    申请日：2020-09-09

    Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Xinchao XU ,  Haifeng WANG ,  Hua WU ,  Zhanyi LIU

    IPC: G06F40/284 ,  G10L15/06 ,  G06N3/08 ,  G10L15/04 ,  G06F40/274

    Abstract: A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. According to an embodiment, the method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model. The technical solution may improve the accuracy of the label marking model.

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