基于深度学习的文本生成简史

Anil Bas, M. O. Topal, Çağdaş Duman, Imke van Heerden
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摘要

自然语言生成是人工智能研究的一个动态领域,其核心是现实文本的自动生成。为了帮助浏览这个庞大而迅速发展的工作体,该研究提供了文本生成历史上值得注意的阶段的简要概述。为此,本文为广大受众描述了深度学习模型,重点是传统的、卷积的、循环的和生成的对抗网络,以及变压器架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Brief History of Deep Learning-Based Text Generation
A dynamic domain in Artificial Intelligence research, Natural Language Generation centres on the automatic generation of realistic text. To help navigate this vast and swiftly developing body of work, the study provides a concise overview of noteworthy stages in the history of text generation. To this end, the paper describes deep learning models for a broad audience, focusing on traditional, convolutional, recurrent and generative adversarial networks, as well as transformer architecture.
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