A multi-agent LLM system using iterative planning and combinatorial innovation produces NLP research ideas with greater diversity and novelty than prior baselines, with quality between accepted and rejected conference papers.
All data used in this study are publicly released by the conference organizers and can be accessed programmatically without authentication
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Enhancing Research Idea Generation through Combinatorial Innovation and Multi-Agent Iterative Search Strategies
A multi-agent LLM system using iterative planning and combinatorial innovation produces NLP research ideas with greater diversity and novelty than prior baselines, with quality between accepted and rejected conference papers.