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LEAP reveals that separating evidence evaluation can drastically enhance the accuracy and interpretability of probabilistic forecasts in LLM applications.
LLMs can move beyond simply assisting static analysis to orchestrating it, enabling the discovery of critical zero-day vulnerabilities.
