Embedding Model
Also called: Embedding Encoder, Vector Embedding Model
A machine learning model that converts text, images, audio, or other data into dense numerical vector representations that capture semantic meaning for retrieval, similarity search, and related AI tasks.
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Related terms
The process of converting text, images, or other data into dense numerical vector representations that capture semantic meaning for retrieval, similarity search, and downstream AI tasks.
Dense RetrievalA retrieval technique that uses dense vector embeddings to identify semantically relevant documents based on similarity in an embedding space.
Semantic SearchA search technique that analyzes sentence meaning and intent rather than matching literal keywords.
Cross EncoderA neural reranking model that jointly encodes a query and a candidate document to produce a highly accurate relevance score.