Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Dongling Xiao

Yu Sun

Han Zhang

Hao Tian

Yukun Li

Haifeng Wang

Hua Wu

Weichong Yin

A method for generating a target object is provided. A first discrete encoded sequence corresponding to an original object is generated by performing discrete encoding on the original object. The original object is of an image type, a text type, or a text-image-combined type. A second discrete encode sequence is obtained by inputting the first discrete encoded sequence into a generative model. A target object is generated based on the second discrete encoded sequence. The target object is of an image type or a text type. When the original object is of the image type, the target object is of the text type. When the original object is of the text type, the target object is of the image type.

Method for generating target object, electronic device, and storage medium

The present disclosure proposes a language generation method and apparatus. The method includes: performing encoding processing on an input sequence by using a preset encoder to generate a hidden state vector corresponding to the input sequence; in response to a granularity category of a second target segment being a phrase, decoding a first target segment vector, the hidden state vector, and a position vector corresponding to the second target segment by using N decoders to generate N second target segments; determining a loss value based on differences between respective N second target segments and a second target annotated segment; and performing parameter updating on the preset encoder, a preset classifier, and the N decoders based on the loss value to generate an updated language generation model for performing language generation.

Language generation method and apparatus, electronic device and storage medium

The present disclosure discloses a method and an apparatus for generating a text based on a semantic representation and relates to a field of natural language processing (NLP) technologies. The method for generating the text includes: obtaining an input text, the input text comprising a source text; obtaining a placeholder of an iword to be predicted in a target text; obtaining a vector representation of the iword to be predicted, in which the vector representation of the iword to be predicted is obtained by calculating the placeholder of the iword to be predicted, the source text and 1to (i&#x2212;1)predicted words by employing a self-attention mechanism; and generating an ipredicted word based on the vector representation of the iword to be predicted, to obtain a target text.

Method and apparatus for generating text based on semantic representation, and medium

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Beijing, China

Dongling Xiao