# Self-Consistency

> Self-consistency samples multiple chain-of-thought reasoning paths for the same question and returns the answer that appears most often, rather than relying on a single greedy decode.

- Identifier: PTL-0028
- Category: Reasoning Elicitation
- Canonical URL: https://protologue.com/t/self-consistency/
- Also known as: majority voting, CoT-SC
- Introduced: 2022

## Description

Wang et al. found this majority vote substantially improved chain-of-thought accuracy on arithmetic and commonsense benchmarks. It trades extra inference cost for reliability and is an early form of test-time compute scaling.

## Broader terms

- [Chain-of-Thought Prompting](https://protologue.com/t/chain-of-thought/)

## Narrower terms

- [Universal Self-Consistency](https://protologue.com/t/universal-self-consistency/)

## Related terms

- [Best-of-N Sampling](https://protologue.com/t/best-of-n-sampling/)
- [Test-Time Compute Scaling](https://protologue.com/t/test-time-compute-scaling/)
- [Temperature](https://protologue.com/t/temperature/)

## Sources

- Wang et al. (2022). Self-Consistency Improves Chain of Thought Reasoning in Language Models. https://arxiv.org/abs/2203.11171

## Cite this entry

Protologue. (2026). Self-Consistency. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0028). https://protologue.com/t/self-consistency/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)