Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation

Researchers developed GYWI, a scientific idea generation system that combines author knowledge graphs with retrieval-augmented generation to help Large Language Models generate more controllable and traceable scientific ideas. The system significantly outperforms mainstream LLMs including GPT-4o, DeepSeek-V3, Qwen3-8B, and Gemini 2.5 in metrics like novelty, reliability, and relevance.