Improving a Multi-Step Reasoning System

A team is developing an AI system that solves complex, multi-step problems. To ensure reliability, they plan to use a language model as a verifier. What is the primary advantage of designing this verifier to assess each individual reasoning step in the context of the preceding path, as opposed to only evaluating the final solution?

A development team is creating an AI system to solve multi-step logic puzzles. They implement a verifier language model designed to assess the validity of each reasoning step based on the preceding steps. To improve its performance, they fine-tune this verifier exclusively on a large dataset of perfectly correct reasoning paths. What is the most likely critical flaw in this fine-tuning approach?

Designing an Input for a Code Verifier