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Home/Glossary/Bi-Encoder
AI Glossary Term

What does “Bi-Encoder” mean?

Definition

A model that encodes queries and documents into separate vectors so they can be compared quickly at scale.

Related terms

Encoder
The component of a model that transforms input into latent representations.
Feature Extraction
Converting raw data into informative features that a model can use.
Embedding Model
A model specialized for converting data into vectors used for semantic search, clustering, and retrieval.
BPE (Byte Pair Encoding)
A subword tokenization algorithm that merges the most frequent character pairs into reusable tokens.
AGI (Artificial General Intelligence)
A hypothetical AI system that can perform most intellectual tasks at a human level across many domains.
AI Agent
A software system that can observe, reason, and take actions to achieve a goal, often using tools and memory.

Learn more in our free guides

AutoencodersSparse Autoencoders for InterpretabilityCross-Encoders vs Bi-EncodersSparse Autoencoders for Feature Extraction

See also

Cross-EncoderLLM-as-JudgeHybrid SearchPass@kRerankerMMLUHNSWHumanEval
PreviousCross-EncoderNextLLM-as-Judge
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