{
  "id": "universal-self-consistency",
  "code": "PTL-0029",
  "term": "Universal Self-Consistency",
  "aliases": [],
  "category": "reasoning",
  "definition": "Universal self-consistency extends self-consistency to free-form outputs by asking the model itself to select the most consistent response among several samples, instead of counting exact-match answers.",
  "description": "This makes sampling-and-selecting usable for tasks such as summarization and open-ended question answering, where answers rarely match word for word.",
  "example": null,
  "broader": [
    "self-consistency"
  ],
  "narrower": [],
  "related": [
    "llm-as-a-judge"
  ],
  "introduced": 2023,
  "sources": [
    {
      "title": "Universal Self-Consistency for Large Language Model Generation",
      "authors": "Chen et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2311.17311"
    }
  ],
  "url": "https://protologue.com/t/universal-self-consistency/",
  "citation": "Protologue. (2026). Universal Self-Consistency. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0029). https://protologue.com/t/universal-self-consistency/"
}