A parallel-tempering evolutionary framework for LLM hypothesis search improves both quality and diversity of candidates in molecular, equation, and algorithm discovery under fixed validation budgets.
arXiv preprint arXiv:2501.09274 , year=
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A multi-agent AI system generates novel biomedical hypotheses that show promising experimental validation in drug repurposing for leukemia, new targets for liver fibrosis, and a bacterial gene transfer mechanism.
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Towards Diverse Scientific Hypothesis Search with Large Language Models
A parallel-tempering evolutionary framework for LLM hypothesis search improves both quality and diversity of candidates in molecular, equation, and algorithm discovery under fixed validation budgets.
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Towards an AI co-scientist
A multi-agent AI system generates novel biomedical hypotheses that show promising experimental validation in drug repurposing for leukemia, new targets for liver fibrosis, and a bacterial gene transfer mechanism.