adaptive-trust

This paper introduces Adaptive Tool Trust Calibration (ATTC), a framework that improves tool-integrated reasoning models by enabling them to adaptively decide when to trust or ignore tool results based on code confidence scores. The approach addresses the "Tool Ignored" problem where models incorrectly dismiss correct tool outputs, achieving 4.1-7.5% performance improvements across multiple models and datasets.