Reasoning & Test-Time Compute · 2023
Self-Consistency Improves Chain-of-Thought Reasoning
Improved chain-of-thought accuracy by sampling many reasoning paths and taking the majority-vote answer instead of trusting a single greedy decode, removing the fragility of one-shot reasoning chains.
Editorial record
Plain-language summary
Self-consistency samples multiple diverse reasoning chains for the same question and then marginalizes over the reasoning to pick the answer most paths agree on. Because a correct answer tends to be reachable by several distinct valid derivations while errors are scattered, voting over sampled chains raised accuracy on arithmetic and commonsense benchmarks over standard chain-of-thought. It became a simple, decoding-time add-on for more reliable reasoning at the cost of extra samples.
Knowledge graph
Relationships
Descendants
ExtendsEvidence: Direct
Chain-of-Thought Prompting Elicits Reasoning
Self-consistency votes over many CoT samples
P-221
EnablesEvidence: Strongly supported
The Monte Carlo Method / Metropolis Algorithm
Self-consistency is Monte-Carlo voting
P-221
Source record
Provenance
- Record ID
- P-221
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
- https://arxiv.org/abs/2203.11171
- arXiv:2203.11171
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.