{
  "id": "colbert",
  "code": "PTL-0130",
  "term": "ColBERT",
  "aliases": [
    "late interaction",
    "late-interaction retrieval",
    "multi-vector retrieval"
  ],
  "category": "retrieval-tools",
  "definition": "ColBERT is a retrieval model that embeds every token of the query and of each passage separately and scores relevance by matching each query token to its most similar passage token, an approach called late interaction.",
  "description": "Late interaction sits between single-vector dense retrieval, which is fast but coarse, and cross-encoder reranking, which is accurate but slow. Passage token embeddings can be precomputed and indexed, so ColBERT keeps much of a cross-encoder's precision at search-engine speed, at the cost of larger indexes.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "dense-retrieval",
    "reranking",
    "dspy"
  ],
  "introduced": 2020,
  "added": "2026-10-10",
  "sources": [
    {
      "title": "ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT",
      "authors": "Khattab and Zaharia",
      "year": 2020,
      "url": "https://arxiv.org/abs/2004.12832"
    }
  ],
  "url": "https://protologue.com/t/colbert/",
  "citation": "Protologue. (2026). ColBERT. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0130). https://protologue.com/t/colbert/"
}