Which prompting technique asks the model the same prompt multiple times and takes the most consistent result as the final answer?

Which prompting technique asks the model the same prompt multiple times and takes the most consistent result as the final answer?

• A. Least-to-Most
• B. Tree-of-Thought Prompting (ToT)
• C. Self-Consistency
• D. Generated Knowledge Prompting

Answer: (C)

Self-Consistency focuses on reliability by generating multiple independent responses to the same prompt and then selecting the final answer that appears most often. The idea is that, although individual responses may wander or vary in their reasoning, the correct conclusion tends to emerge as the common outcome across many attempts. By aggregating those runs and taking the most frequent final result, you get a solution that is more robust to randomness in the model’s outputs. This differs from other prompting strategies: least-to-most prompting gradually adds more complex steps to solve a problem, guiding the model from simple to harder subproblems. Tree-of-Thought prompting builds and evaluates a branching set of possible rationales to find a good reasoning path. Generated Knowledge Prompting prompts the model to generate knowledge or facts first, which are then used to answer.

Self-Consistency focuses on reliability by generating multiple independent responses to the same prompt and then selecting the final answer that appears most often. The idea is that, although individual responses may wander or vary in their reasoning, the correct conclusion tends to emerge as the common outcome across many attempts. By aggregating those runs and taking the most frequent final result, you get a solution that is more robust to randomness in the model’s outputs.

This differs from other prompting strategies: least-to-most prompting gradually adds more complex steps to solve a problem, guiding the model from simple to harder subproblems. Tree-of-Thought prompting builds and evaluates a branching set of possible rationales to find a good reasoning path. Generated Knowledge Prompting prompts the model to generate knowledge or facts first, which are then used to answer.