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    METHOD FOR MULTI-TASK SCHEDULING, DEVICE AND STORAGE MEDIUM
    11.
    发明申请
    METHOD FOR MULTI-TASK SCHEDULING, DEVICE AND STORAGE MEDIUM 有权

    公开(公告)号：US20220374775A1

    公开(公告)日：2022-11-24

    申请号：US17867516

    申请日：2022-07-18

    Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

    Inventor： Ji LIU ,  Beichen MA ,  Jingbo ZHOU ,  Ruipu ZHOU ,  Dejing DOU

    IPC: G06N20/00 ,  G06F9/48

    Abstract: A method for multi-task scheduling, a device and a storage medium are provided. The method may include: initializing a list of candidate scheduling schemes, the candidate scheduling scheme being used to allocate a terminal device for training to each machine learning task in a plurality of machine learning tasks; perturbing, for each candidate scheduling scheme in the list of candidate scheduling schemes, the candidate scheduling scheme to generate a new scheduling scheme; determining whether to replace the candidate scheduling scheme with the new scheduling scheme based on a fitness value of the candidate scheduling scheme and a fitness value of the new scheduling scheme, to generate a new scheduling scheme list; and determining a target scheduling scheme, based on the fitness value of each new scheduling scheme in the new scheduling scheme list.

    DATA QUERY METHOD AND APPARATUS BASED ON LARGE MODEL, ELECTRONIC DEVICE, AND STORAGE MEDIUM
    13.
    发明申请
    DATA QUERY METHOD AND APPARATUS BASED ON LARGE MODEL, ELECTRONIC DEVICE, AND STORAGE MEDIUM 有权

    公开(公告)号：US20250103589A1

    公开(公告)日：2025-03-27

    申请号：US18974155

    申请日：2024-12-09

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

    Inventor： Yixiong XIAO ,  Jingbo ZHOU

    IPC: G06F16/242

    Abstract: Data query method and apparatus based on large model, an electronic device, and a storage medium are disclosed, which relates to the field of artificial intelligence, specifically in natural language processing, deep learning, and large model technologies, applicable to scenarios such as dialogue systems and information retrieval. The method includes: performing entity recognition on a query to obtain the target entity in the query; obtaining a first related content associated with the target entity from internal information, and performing data analysis on the first related content using a large language model (LLM) to obtain a data analysis result; obtaining a second related content associated with the target entity from external information, and performing data generation on the second related content using the LLM to obtain a data generation result; obtaining a query result corresponding to the query based on the data analysis result and the data generation result.

    DRUG REACTION PREDICTION AND MODEL TRAINING METHOD, APPARATUS AND DEVICE
    14.
    发明申请
    DRUG REACTION PREDICTION AND MODEL TRAINING METHOD, APPARATUS AND DEVICE 有权

    公开(公告)号：US20250014766A1

    公开(公告)日：2025-01-09

    申请号：US18895554

    申请日：2024-09-25

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

    Inventor： Jingbo ZHOU ,  Yuhan YE

    IPC: G16H70/40 ,  G06N20/00

    Abstract: A drug reaction prediction method, which is related to the field of artificial intelligence, specifically involving deep learning, computational biology, and chemistry, is disclosed. The drug reaction prediction method includes: obtaining a target graph based on multiple levels of entities contained in a drug to be predicted; the target graph includes an entity graph representing topological information within the entities and an interaction graph representing correlation information between the entities; performing representation extraction processing on the target graph to obtain an initial representation; obtaining a target representation based on a predetermined prompt identifier and the initial representation; and obtaining a drug reaction prediction result for the drug to be predicted based on the target representation.

    DATA UPDATING METHOD, MODEL TRAINING METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM
    15.
    发明公开
    DATA UPDATING METHOD, MODEL TRAINING METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM 审中-公开

    公开(公告)号：US20240282103A1

    公开(公告)日：2024-08-22

    申请号：US18654477

    申请日：2024-05-03

    Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

    Inventor： Congxi XIAO ,  Jizhou HUANG ,  Jingbo ZHOU

    IPC: G06V20/10 ,  G06V10/26 ,  G06V10/74 ,  G06V10/82

    CPC classification number: G06V20/176 ,  G06V10/26 ,  G06V10/761 ,  G06V10/82

    Abstract: A data updating method, a model training method and related devices are provided. The method includes obtaining urban graph data in a preset region, the urban graph data including a node set including central nodes, an edge set and a feature set, the edge set including neighborhoods corresponding to the central nodes, the neighborhoods including other nodes possessing connecting edges with the central nodes, the neighborhoods corresponding to a target region, and the feature set including node features of the nodes in the node set; partitioning the target region into at least two sub-regions to obtain a region partition set; aggregating the node features corresponding to all nodes located within the same sub-region to obtain the regional features of each of the sub-regions; updating the node features of the central node based on the regional features of the sub-regions in the region partition set to obtain target feature data.

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