IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation

Large Language Models (LLMs) have significantly automated the process of scientific discovery over the past few years. However, existing systems share one core limitation: they generate and optimize ideas independently for either Quality or Diversity. This often leads to the generation of ideas in close proximity to one another or to a large set of trivial, unsound, or unclear concepts. In this work, we instead argue that research ideation should be treated as a conjunction of both objectives an

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ethics.ai (24 July 2026), “IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation,” evidence record 13698, https://ethics.ai/record/13698 (originally published by arXiv cs.AI).

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