Advances and challenges in artificial intelligence text generation

Bing LI; Peng YANG; Yuankang SUN; Zhongjian HU; Meng YI

doi:10.1631/FITEE.2300410

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Front. Inform. Technol. Electron. Eng ›› 2024, Vol. 25 ›› Issue (1) : 64-83. DOI: 10.1631/FITEE.2300410

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Advances and challenges in artificial intelligence text generation

Bing LI¹^,² ,
Peng YANG¹^,² ,
Yuankang SUN¹^,² ,
Zhongjian HU¹^,² ,
Meng YI¹^,²

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Abstract

Text generation is an essential research area in artificial intelligence (AI) technology and natural language processing and provides key technical support for the rapid development of AI-generated content (AIGC). It is based on technologies such as natural language processing, machine learning, and deep learning, which enable learning language rules through training models to automatically generate text that meets grammatical and semantic requirements. In this paper, we sort and systematically summarize the main research progress in text generation and review recent text generation papers, focusing on presenting a detailed understanding of the technical models. In addition, several typical text generation application systems are presented. Finally, we address some challenges and future directions in AI text generation. We conclude that improving the quality, quantity, interactivity, and adaptability of generated text can help fundamentally advance AI text generation development.

Keywords

AI text generation / Natural language processing / Machine learning / Deep learning

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Bing LI, Peng YANG, Yuankang SUN, Zhongjian HU, Meng YI. Advances and challenges in artificial intelligence text generation. Front. Inform. Technol. Electron. Eng, 2024, 25(1): 64‒83 https://doi.org/10.1631/FITEE.2300410