Cross-Encoder
A Cross-Encoder is a neural network architecture used in information retrieval that processes the query and the candidate document together as a single input sequence, computing attention across both to produce a highly accurate relevance score.
Frequently Asked Questions
What is the difference between a Bi-Encoder and a Cross-Encoder?▼
A Bi-Encoder embeds queries and documents separately (used for fast vector search). A Cross-Encoder embeds them together, which is slow but highly accurate.
Why not use Cross-Encoders for the initial retrieval phase?▼
Because processing millions of documents through a Cross-Encoder for every query is too computationally slow. It is only viable for reranking a small candidate set (e.g. top 50).
Quick Facts
- CategoryInformation Retrieval
- Key ApplicationRAG reranking, document classification, and similarity scoring.
Coverage Trend12 Weeks
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