Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces
The Filtered Reasoning Score (FRS) evaluates reasoning quality by focusing only on a model's most confident outputs, rather than just final accuracy. It uses a confidence-conditioned process metric to uncover hidden structures in reasoning. FRS helps identify models with similar accuracy but different underlying reasoning abilities, providing a more reliable pre-deployment audit.