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ColBERT

ColBERT (Contextualized Late Interaction over BERT) is a retrieval model that utilizes a late interaction architecture to encode queries and documents into multi-vector representations at the token level. It enables high-precision retrieval in RAG pipelines by calculating the MaxSim (maximum similarity) between token sets, capturing fine-grained semantic nuances that single-vector bi-encoders often lose.

Definition

ColBERT (Contextualized Late Interaction over BERT) is a retrieval model that utilizes a late interaction architecture to encode queries and documents into multi-vector representations at the token level. It enables high-precision retrieval in RAG pipelines by calculating the MaxSim (maximum similarity) between token sets, capturing fine-grained semantic nuances that single-vector bi-encoders often lose.

Disambiguation

Unlike standard bi-encoders that produce one vector per document, ColBERT produces a matrix of vectors per document.

Visual Metaphor

"A transparent overlay of two star maps where every individual star is checked for a match, rather than just comparing the center points of the galaxies."

Key Tools
RAGatouilleDSPyVespaStanford ColBERT LibraryPLAID
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Conceptual Overview

ColBERT (Contextualized Late Interaction over BERT) is a retrieval model that utilizes a late interaction architecture to encode queries and documents into multi-vector representations at the token level. It enables high-precision retrieval in RAG pipelines by calculating the MaxSim (maximum similarity) between token sets, capturing fine-grained semantic nuances that single-vector bi-encoders often lose.

Disambiguation

Unlike standard bi-encoders that produce one vector per document, ColBERT produces a matrix of vectors per document.

Visual Analog

A transparent overlay of two star maps where every individual star is checked for a match, rather than just comparing the center points of the galaxies.

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