{
  "id": "emergent-abilities",
  "code": "PTL-0184",
  "term": "Emergent Abilities",
  "aliases": [
    "emergence",
    "emergent capabilities"
  ],
  "category": "foundations",
  "definition": "Emergent abilities are capabilities that appear in large language models above a certain scale but are near chance in smaller ones, such as multi-step arithmetic or benefiting from chain-of-thought prompting.",
  "description": "The idea explained why some prompting techniques only work with large models. It is disputed. Later analysis argued that many apparent jumps are artifacts of all-or-nothing metrics such as exact match, and that smoother metrics show gradual improvement with scale. The practical lesson stands either way, which is that a technique that fails on a small model may work on a larger one, and the reverse.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "large-language-model",
    "chain-of-thought",
    "in-context-learning",
    "benchmark"
  ],
  "introduced": 2022,
  "added": "2026-10-10",
  "sources": [
    {
      "title": "Emergent Abilities of Large Language Models",
      "authors": "Wei et al.",
      "year": 2022,
      "url": "https://arxiv.org/abs/2206.07682"
    },
    {
      "title": "Are Emergent Abilities of Large Language Models a Mirage?",
      "authors": "Schaeffer et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2304.15004"
    }
  ],
  "url": "https://protologue.com/t/emergent-abilities/",
  "citation": "Protologue. (2026). Emergent Abilities. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0184). https://protologue.com/t/emergent-abilities/"
}