公开(公告)号：US20200250377A1

公开(公告)日：2020-08-06

申请号：US16856450

申请日：2020-04-23

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xin Jiang ,  Lifeng Shang ,  Hang Li ,  Zichao Li

IPC: G06F40/289

Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.

公开(公告)号：US11586814B2

公开(公告)日：2023-02-21

申请号：US16856450

申请日：2020-04-23

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xin Jiang ,  Lifeng Shang ,  Hang Li ,  Zichao Li

IPC: G06F40/289 ,  G06F40/237

Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.

公开(公告)号：US20230229898A1

公开(公告)日：2023-07-20

申请号：US18186942

申请日：2023-03-20

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Zichao Li ,  Lu Hou ,  Xin Jiang

IPC: G06N3/0499 ,  G06N3/08

CPC classification number: G06N3/0499 ,  G06N3/08

Abstract: A data processing method includes: obtaining to-be-processed data and a target neural network model, where the target neural network model includes a first transformer layer, the first transformer layer includes a first residual branch and a second residual branch, the first residual branch includes a first attention head, and the second residual branch includes a target feed-forward network (FFN) layer; and performing target task related processing on the to-be-processed data based on the target neural network model, to obtain a data processing result, where the target neural network model is for performing a target operation on an output of the first attention head and a first weight value to obtain an output of the first residual branch, and/or the target neural network model is for performing a target operation on an output of the target FFN and a second weight value to obtain an output of the second residual branch.