{
  "id": "self-consistency",
  "code": "PTL-0028",
  "term": "Self-Consistency",
  "aliases": [
    "majority voting",
    "CoT-SC"
  ],
  "category": "reasoning",
  "definition": "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.",
  "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.",
  "example": null,
  "broader": [
    "chain-of-thought"
  ],
  "narrower": [
    "universal-self-consistency"
  ],
  "related": [
    "best-of-n-sampling",
    "test-time-compute-scaling",
    "temperature"
  ],
  "introduced": 2022,
  "sources": [
    {
      "title": "Self-Consistency Improves Chain of Thought Reasoning in Language Models",
      "authors": "Wang et al.",
      "year": 2022,
      "url": "https://arxiv.org/abs/2203.11171"
    }
  ],
  "url": "https://protologue.com/t/self-consistency/",
  "citation": "Protologue. (2026). Self-Consistency. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0028). https://protologue.com/t/self-consistency/"
}