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A verifier operating at the step-level can produce various forms of output to guide the reasoning process. Similar to verifiers that evaluate complete solutions, these outputs can include a quantitative numerical score, a qualitative categorical label, or descriptive textual feedback.

Outputs of a Step-Level Verifier

A team is developing a system to solve multi-step logic puzzles. The system generates one reasoning step at a time. After each step, a verifier assesses it and provides a simple 'valid' or 'invalid' label. The team observes that the system often gets stuck in long, unproductive reasoning paths, even when all the individual steps are technically 'valid'. Based on this scenario, which type of verifier output would be most effective at guiding the system towards more efficient solutions, and why?

Improving a Step-by-Step Reasoning System

A team is developing a system that generates step-by-step solutions to problems. They are using a verifier to check each step. Match each type of verifier output with the primary goal it is best suited to achieve.

Imagine a system where a large language model generates a step-by-step solution to a complex physics problem. At one step, the model correctly identifies the formula for kinetic energy but incorrectly uses the mass in grams instead of kilograms. To enable the model to make a precise correction and continue, which form of output from a step-level verifier would be most effective?

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