A randomized execution study with 43 experts shows that LLM-generated research ideas lose more of their appeal than human ideas when actually implemented, reversing part of their ideation-stage advantage.
MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
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The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
A randomized execution study with 43 experts shows that LLM-generated research ideas lose more of their appeal than human ideas when actually implemented, reversing part of their ideation-stage advantage.