“Researchers propose using conformal prediction to quantify uncertainty in Large Reasoning Models, providing statistically rigorous guarantees for complex reasoning tasks. This addresses a critical gap in LRM reliability, enabling safer deployment in high-stakes applications where understanding model confidence is essential.”