TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping

This paper introduces TRACES, a lightweight framework designed to optimize Language Reasoning Models (LRMs) by tagging reasoning steps in real-time. It enables adaptive, cost-efficient early stopping of LRM inferences, addressing their current inefficiency and over-generation of verification steps.