Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Zhe Hu

Xinyan Xiao

Jiachen Liu

Hua Wu

Cheng Peng

Xuefeng Luo

Zhiwei Cao

A method of generating a text, a method of training a text generation model, an electronic device, and a storage medium, which relate to a field of a computer technology, in particular to fields of deep learning and natural language processing technologies. A specific implementation solution includes: determining a reference feature representation of a target semantic information; determining, based on the reference feature representation and at least one predetermined logical character, at least one sentence latent representation respectively corresponding to the at least one predetermined logical character; and generating a target text content based on the at least one sentence latent representation.

Method of generating text, method of training model, electronic device, and medium

The disclosure provides a method for generating a text. The method includes: obtaining a coding sequence of a first text by coding the first text; obtaining a controllable attribute of a second text to be generated; predicting a hidden state of the second text based on the coding sequence of the first text and the controllable attribute of the second text; and obtaining a second text corresponding to the first text by decoding the coding sequence of the first text based on the hidden state of the second text.

Method and apparatus for generating a text, and storage medium

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.

Implementing text generation

The present disclosure discloses a method and apparatus for processing a dataset. The method includes: obtaining a first text set meeting a preset similarity matching condition with a target text from multiple text blocks provided by a target user; obtaining a second text set from the first text set, in which each text in the second text set does not belong to a same text block as the target text; generating a negative sample set of the target text based on content of a candidate text block to which each text in the second text set belongs; generating a positive sample set of the target text based on content of a target text block to which the target text belongs; and generating a dataset of the target user based on the negative sample set and the positive sample set, and training a matching model based on the dataset.

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Beijing, China

Zhe Hu