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It is shown that physics-informed search can complement benchmark-based evaluation by uncovering hidden failure modes by uncovering hidden failure modes in MLIP Detective, an agentic framework for active failure mode discovery.
Capped evaluation reveals that many high scores from coding agents are just clever shortcuts, not true problem-solving.