This systematic review aims to provide a comprehensive analysis of the state of data-to-text generation research, focusing on identifying research gaps, offering future directions, and addressing challenges found during the review. We thoroughly examined the literature, including approaches, datasets, evaluation metrics, applications, multilingualism, and hallucination mitigation measures. Our review provides a roadmap for future research in this rapidly evolving field.

翻译：本系统性综述旨在全面分析数据到文本生成领域的研究现状，重点关注识别研究空白、提出未来方向以及解决综述过程中发现的挑战。我们深入梳理了相关文献，涵盖方法、数据集、评估指标、应用、多语言处理以及幻觉缓解措施。本综述为这一快速发展的领域提供了未来研究的路线图。