Vibe researching is an emerging paradigm in which human researchers provide high-level direction and critical judgment while LLM-based agents handle the labor-intensive execution of literature review, experimentation, data analysis, and manuscript drafting. Inspired by the "vibe coding" movement in software engineering, it occupies a middle ground between traditional manual research and fully autonomous AI research systems. This paper defines the concept, describes its methodology (multi-agent architectures, memory, tool use, retrieval-augmented generation, and the human's role as orchestrator), identifies seven technical limitations, weighs its positive and negative societal impacts, and maps each problem to a concrete future direction. Our goal is to provide the research community with a clear and honest map of the territory so that the conversation about responsible adoption can start from shared ground.

翻译：“氛围研究”是一种新兴范式，其中人类研究者提供高层方向与关键判断，而基于大语言模型的智能体承担文献综述、实验执行、数据分析及草稿撰写等劳动密集型工作。受软件工程领域“氛围编程”运动的启发，它介于传统人工研究与全自主人工智能研究系统之间。本文定义了这一概念，描述了其方法论（包括多智能体架构、记忆、工具使用、检索增强生成以及人类作为协调者的角色），识别出七项技术局限，权衡了其积极与消极社会影响，并将每个问题对应到具体的未来方向。我们的目标是向研究社区提供一份关于该领域的清晰而诚实的图景，以便关于负责任应用这一概念的讨论能从共同的起点开始。