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.

翻译：ChatGPT 及其他前沿大型语言模型（LLMs）正在迅速改变多个领域，为广泛的应用提供了强大工具。这些模型通常基于海量数据集训练，展现出类人的文本生成能力，使其能够用于构思、文献综述、编程、草拟文稿及科学传播等研究任务。我们开展了一项历时数月的研究，邀请了来自不同职业阶段与研究领域的13位天文学家，以探索LLMs在多样化任务中的应用，并评估其在研究相关活动中的表现。此项工作同时辅以一项匿名调查，用于评估参与者对LLMs的使用体验与态度。我们对尝试完成的任务及调查反馈进行了详细分析，并提供了具体的输出示例。我们的研究结果既揭示了LLMs在辅助研究方面的潜力与局限，也探讨了通用层面及研究领域特有的伦理考量。最后，我们提出一系列建议，强调研究者需以批判性思维与领域专业知识作为LLMs的补充，确保这些工具成为严谨科学探究的助力而非替代品。