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.

系统综述研究数据到文本生成的现状，包括研究空白、未来方向、挑战以及对应措施，并提供了这个快速发展领域中未来研究的路线图。

数据到文本自然语言生成的系统性综述

A Systematic Review of Data-to-Text NLG

Through iterative, cross-disciplinary discussions, we define and propose
next-steps for Human-centered Generative AI (HGAI) from a technical
perspective. We contribute a roadmap that lays out future directions of
Generative AI spanning three levels: Aligning with human values; Accommodating
humans' expression of intents; and Augmenting humans' abilities in a
collaborative workflow. This roadmap intends to draw interdisciplinary research
teams to a comprehensive list of emergent ideas in HGAI, identifying their
interested topics while maintaining a coherent big picture of the future work
landscape.

通过跨学科讨论，我们从技术角度定义和提出了人类中心生成式人工智能的下一步研究方向，贡献了一份旨在吸引跨学科研究小组关注 HGAI 的新生代思路清单，指明了他们感兴趣的话题，同时保持未来工作格局的连贯性。

面向人类中心的生成式 AI 的下一步：技术视角

Next Steps for Human-Centered Generative AI: A Technical Perspective

This article presents a comprehensive overview of the digital twin technology
and its capability levels, with a specific focus on its applications in the
wind energy industry. It consolidates the definitions of digital twin and its
capability levels on a scale from 0-5; 0-standalone, 1-descriptive,
2-diagnostic, 3-predictive, 4-prescriptive, 5-autonomous. It then, from an
industrial perspective, identifies the current state of the art and research
needs in the wind energy sector. The article proposes approaches to the
identified challenges from the perspective of research institutes and offers a
set of recommendations for diverse stakeholders to facilitate the acceptance of
the technology. The contribution of this article lies in its synthesis of the
current state of knowledge and its identification of future research needs and
challenges from an industry perspective, ultimately providing a roadmap for
future research and development in the field of digital twin and its
applications in the wind energy industry.

本文从 0-5 的层次对数字孪生技术的定义及其能力水平进行了综合概述，着重介绍了其在风能行业中的应用。从工业角度出发，确定了当前风能领域的现状和研究需求，并从研究机构的角度提出了解决这些挑战的方法，并为促进科技接受提供了一组建议，为数字孪生技术和其在风能行业应用的未来研究和发展提供了路线图。

风能中的数字孪生：新兴技术和行业指导未来方向

Digital Twins in Wind Energy: Emerging Technologies and  Industry-Informed Future Directions

Asymptotic properties of statistical estimators play a significant role both
in practice and in theory. However, many asymptotic results in statistics rely
heavily on the independent and identically distributed (iid) assumption, which
is not realistic when we have fixed designs. In this article, we build a
roadmap of general procedures for deriving asymptotic properties under fixed
designs and the observations need not to be iid. We further provide their
applications in many statistical applications. Finally, we apply our results to
Poisson regression using a COVID-19 dataset as an illustration to demonstrate
the power of these results in practice.

本篇文章研究了在固定设计下，不满足独立同分布假设的情况下，建立渐近性质的一般程序，并将其应用于许多统计应用中，最终通过使用 COVID-19 数据集对 Poisson 回归进行了实证分析。