问HN：用AI进行“氛围研究”——有人真的在使用吗？
“氛围研究”（vibe researching）的概念——利用人工智能快速探索、综合文献，并生成新颖的研究想法或框架——看起来很有前景。它不仅仅是文献综述，还可以作为头脑风暴的辅助工具。
这里有没有人认真使用过人工智能（例如，Claude用于长篇论文分析、arXiv上的定制GPT或专业代理）来帮助生成假设、识别研究空白或撰写论文的实质性部分？
关于准确性、引用的幻觉或对复杂理论的肤浅理解，最大的陷阱是什么？你是如何验证人工智能输出的？
你认为它是早期研究的一个合法加速器，还是更多地作为处理日常任务的生产力工具？有没有成功案例将其与具体的研究成果联系起来？
期待来自学术界、行业研究人员或独立探索者的真实经验分享。
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The concept of "vibe researching" – using AI to rapidly explore, synthesize literature, and generate novel research ideas or frameworks – seems promising. Beyond just literature reviews, it could act as a brainstorming co-pilot.<p>Has anyone here seriously used AI (e.g., Claude for long-context paper analysis, custom GPTs on arXiv, or specialized agents) to aid in hypothesis generation, research gap identification, or drafting substantive parts of a paper?<p>What are the biggest pitfalls regarding accuracy, hallucination of citations, or superficial understanding of complex theory? How do you validate the AI's output?<p>Do you see it as a legitimate accelerator for early-stage research, or more of a productivity tool for mundane tasks? Any success stories linking it to a tangible research outcome?<p>Looking for honest experiences from academics, industry researchers, or solo discoverers.