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ICLR 2026Blog Track PosterAccept (Poster)

Heuristic-Based Ideation for Guiding LLMs Toward Structured Creativity

Xiao Liu, Haokun Liu, Chenhao Tan

University of Chicago

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摘要

Large Language Models (LLMs) hold immense promise for accelerating scientific discovery, yet current LLM-based ideation methods often rely on ad-hoc strategies rather than systematic frameworks. This blog introduces Ideation Heuristics, a systematic approach that formalizes 20 cognitive heuristics that structure how researchers generate new ideas. We show that researchers across disciplines find these heuristics highly useful, and we demonstrate how they can be operationalized through Claude skills.