标题： 理解LLM化CHI：通过系统文献综述剖析LLMs对CHI的影响 显示英文标题

标题： Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review

摘要： 大型语言模型（LLMs）被定位为将彻底改变人机交互（HCI），不仅重塑我们研究的界面、设计模式和社会技术系统，还重塑我们使用的研究实践。然而到目前为止，人们对LLMs在HCI中的采用仍了解甚少。我们通过系统文献综述了2020-24年间153篇涉及LLMs的CHI论文来弥补这一空白。我们对以下方面进行了分类：（1）LLMs应用的领域；（2）LLMs在HCI项目中的角色；（3）贡献类型；以及（4）已知的局限性和风险。我们发现LLM工作涉及10个不同的领域，主要通过实证和成果贡献。作者在五个不同的角色中使用LLM，包括作为研究工具或模拟用户。然而，作者经常提出有效性和可重复性问题，并且绝大多数研究的是封闭模型。我们概述了利用LLM改进HCI研究的机会，并为研究人员提供了考虑LLM相关工作的有效性和适当性的指导问题。 显示英文摘要

摘要： Large language models (LLMs) have been positioned to revolutionize HCI, by reshaping not only the interfaces, design patterns, and sociotechnical systems that we study, but also the research practices we use. To-date, however, there has been little understanding of LLMs' uptake in HCI. We address this gap via a systematic literature review of 153 CHI papers from 2020-24 that engage with LLMs. We taxonomize: (1) domains where LLMs are applied; (2) roles of LLMs in HCI projects; (3) contribution types; and (4) acknowledged limitations and risks. We find LLM work in 10 diverse domains, primarily via empirical and artifact contributions. Authors use LLMs in five distinct roles, including as research tools or simulated users. Still, authors often raise validity and reproducibility concerns, and overwhelmingly study closed models. We outline opportunities to improve HCI research with and on LLMs, and provide guiding questions for researchers to consider the validity and appropriateness of LLM-related work.