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The paper introduces the Paper Assistant Tool (PAT), an agentic AI framework for deep scientific review that uses inference scaling to identify mathematical errors and other flaws, achieving a 34% improvement in recall over zero-shot methods. Pilot deployments at STOC and ICML demonstrate its ability to catch critical errors before submission, easing the burden on human referees.