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Large Language Models for Scientific Idea Generation: A Creativity-Centered Survey

arXiv — cs.CL•Wednesday, November 12, 2025 at 5:00:00 AM
NeutralArtificial Intelligence
The recent survey titled 'Large Language Models for Scientific Idea Generation' sheds light on the evolving role of large language models (LLMs) in generating scientific ideas, a process fundamental to scientific discovery and human progress. The survey categorizes various methods into five families: External knowledge augmentation, Prompt-based distributional steering, Inference-time scaling, Multi-agent collaboration, and Parameter-level adaptation. This structured synthesis aims to balance creativity with scientific soundness, recognizing that the novelty of contributions is as crucial as their empirical validity. Despite their promise, the creative capacity of LLMs remains inconsistent and poorly understood, highlighting the need for further exploration. The frameworks of Boden's taxonomy and Rhodes' 4Ps are employed to interpret the contributions of these models, underscoring their potential to reshape scientific research and innovation.
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