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.
Others employ retrieval-augmented generation frameworks to dynamically integrate external knowledge during the idea construction process (Si et al., 2024)
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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.