An LLM pipeline that recombines mined themes, domains, and methods generates diverse research ideas, with 99.5% of surveyed papers decomposable into these three axes but only 16.4% reconstructible from them.
By prompting the model to generate adversarial examples that contradict stereotypes, we can encourage it to develop more nuanced and less biased representations
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The Ramon Llull's Thinking Machine for Automated Ideation
An LLM pipeline that recombines mined themes, domains, and methods generates diverse research ideas, with 99.5% of surveyed papers decomposable into these three axes but only 16.4% reconstructible from them.