ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text generation capabilities, making them useful for research tasks such as ideation, literature review, coding, drafting, and outreach. We conducted a study involving 13 astronomers at different career stages and research fields to explore LLM applications across diverse tasks over several months and to evaluate their performance in research-related activities. This work was accompanied by an anonymous survey assessing participants' experiences and attitudes towards LLMs. We provide a detailed analysis of the tasks attempted and the survey answers, along with specific output examples. Our findings highlight both the potential and limitations of LLMs in supporting research while also addressing general and research-specific ethical considerations. We conclude with a series of recommendations, emphasizing the need for researchers to complement LLMs with critical thinking and domain expertise, ensuring these tools serve as aids rather than substitutes for rigorous scientific inquiry.

本研究针对大型语言模型（LLMs）在天文学研究中应用的潜在问题与局限性展开探讨。通过对13位不同职业阶段天文学家的研究，分析了LLMs在多种研究任务中的使用效果及参与者的体验。研究表明，虽然LLMs在协助研究方面展现出巨大潜力，但仍需结合研究者的批判性思维和专业知识，以确保其作为辅助工具而非科学探究的替代品。

大型语言模型在天文学研究演变中的作用