LLM-based agents offer new potential to accelerate science and reshape research work. However, the quality of researcher contributions can vary significantly depending on human ability to steer agent behaviors. How can we best use these tools to augment scientific creativity without undermining aspects of contribution and ownership that drive research? To investigate this, we developed an agentic research ideation system integrating three roles -- Ideator, Writer, and Evaluator -- across three control levels -- Low, Medium, and Intensive. Our mixed-methods study with 54 researchers suggests three key findings in how LLM-based agents reshape scientific creativity: 1) perceived creativity support does not simply increase linearly with greater control; 2) human effort shifts from ideating to verifying ideas; and 3) ownership becomes a negotiated outcome between human and AI. Our findings suggest that LLM agent design should emphasize researcher empowerment, fostering a sense of ownership over strong ideas rather than reducing researchers to operating an automated AI-driven process.

翻译：基于LLM的智能体为加速科学进程和重塑研究工作提供了新的潜力。然而，研究者贡献的质量可能因其引导智能体行为的能力差异而显著不同。我们如何才能最佳地利用这些工具来增强科学创造力，同时又不损害驱动研究的贡献与所有权要素？为探究此问题，我们开发了一个智能体研究构思系统，该系统整合了三种角色——构思者、撰写者和评估者——并设置了三个控制级别：低度、中度和深度控制。我们与54位研究者进行的混合方法研究揭示了基于LLM的智能体重塑科学创造力的三个关键发现：1）感知到的创造力支持并非简单地随控制程度的增加而线性提升；2）人类努力从构思想法转向验证想法；3）所有权成为人类与AI协商的结果。我们的研究结果表明，LLM智能体设计应强调研究者的赋能，培养其对优质想法的所有权感，而非将研究者降格为操作自动化AI驱动过程的角色。