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1.
公开(公告)号:US11803751B2
公开(公告)日:2023-10-31
申请号:US17140863
申请日:2021-01-04
申请人: Google LLC
发明人: Mohammad Saleh , Jingqing Zhang , Yao Zhao , Peter J. Liu
摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network. One of the methods includes pre-training the text summarization neural network including learning values of a plurality of network parameters through self-supervised learning using unlabeled data comprising unlabeled first texts, the pre-training including: obtaining an unlabeled first text comprising a plurality of segments; selecting one or more of the plurality of segments; processing a masked first text that excludes the one or more selected segments to generate a prediction of the one or more selected segments; and determining, based on a difference between the prediction and the one or more selected segments, an update to the current values of the plurality of network parameters; adapting the pre-trained text summarization neural network for a specific text summarization task using labeled data comprising second texts and respective summaries of the second texts.
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2.
公开(公告)号:US20240185065A1
公开(公告)日:2024-06-06
申请号:US18485950
申请日:2023-10-12
申请人: Google LLC
发明人: Mohammad Saleh , Jingqing Zhang , Yao Zhao , Peter J. Liu
摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network. One of the methods includes pre-training the text summarization neural network including learning values of a plurality of network parameters through self-supervised learning using unlabeled data comprising unlabeled first texts, the pre-training including: obtaining an unlabeled first text comprising a plurality of segments; selecting one or more of the plurality of segments; processing a masked first text that excludes the one or more selected segments to generate a prediction of the one or more selected segments; and determining, based on a difference between the prediction and the one or more selected segments, an update to the current values of the plurality of network parameters; adapting the pre-trained text summarization neural network for a specific text summarization task using labeled data comprising second texts and respective summaries of the second texts.
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3.
公开(公告)号:US10885436B1
公开(公告)日:2021-01-05
申请号:US16869419
申请日:2020-05-07
申请人: Google LLC
发明人: Mohammad Saleh , Jingqing Zhang , Yao Zhao , Peter J. Liu
摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network. One of the methods includes pre-training the text summarization neural network including learning values of a plurality of network parameters through self-supervised learning using unlabeled data comprising unlabeled first texts, the pre-training including: obtaining an unlabeled first text comprising a plurality of segments; selecting one or more of the plurality of segments; processing a masked first text that excludes the one or more selected segments to generate a prediction of the one or more selected segments; and determining, based on a difference between the prediction and the one or more selected segments, an update to the current values of the plurality of network parameters; adapting the pre-trained text summarization neural network for a specific text summarization task using labeled data comprising second texts and respective summaries of the second texts.
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4.
公开(公告)号:US20210350229A1
公开(公告)日:2021-11-11
申请号:US17140863
申请日:2021-01-04
申请人: Google LLC
发明人: Mohammad Saleh , Jingqing Zhang , Yao Zhao , Peter J. Liu
摘要: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network. One of the methods includes pre-training the text summarization neural network including learning values of a plurality of network parameters through self-supervised learning using unlabeled data comprising unlabeled first texts, the pre-training including: obtaining an unlabeled first text comprising a plurality of segments; selecting one or more of the plurality of segments; processing a masked first text that excludes the one or more selected segments to generate a prediction of the one or more selected segments; and determining, based on a difference between the prediction and the one or more selected segments, an update to the current values of the plurality of network parameters; adapting the pre-trained text summarization neural network for a specific text summarization task using labeled data comprising second texts and respective summaries of the second texts.
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