Cross-encoders: An End-to-end Guide

Hosted by Radu Gheorghe and Trey Grainger

Wed, Jun 17, 2026

4:00 PM UTC (1 hour)

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AI-Powered Search: Modern Retrieval for Humans & Agents
Trey Grainger and Doug Turnbull
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What you'll learn

What are cross-encoders and their uses?

As a form of ranking classifier, cross encoders are an essential tool for search relevance ranking.

Trade-offs using cross-encoders vs. standard vector search

Compared to regular vector search (with bi-encoders), cross-encoders greatly improve semantic ranking, but at a cost.

An end-to-end walkthrough of using cross-encoders (in Vespa)

Exporting the cross-encoder model (ONNX format), tokenizing doc and query text, & connecting the dots in a rank profile.

Tips and tricks to keep latency and cost in check

Optimization tricks like using multi-stage ranking and running the cross-encoder on a GPU.

Why this topic matters

Cross-encoders usually outperform traditional vector search at relevance ranking, because they can capture deep nuances of the query-to-document relationship. They are usually very expensive to run compute and latency-wise, however. For best performance, you need to keep this computation close to the data, implement cross-encoders

You'll learn from

Radu Gheorghe

Software Engineer, Vespa.ai

Radu has been in the search space for many years, mainly on Elasticsearch, Solr, OpenSearch, and, more recently, Vespa.ai. Helps users with both the relevance and the operations side of retrieval. Enjoys education in all its forms (training, blog posts, books, conferences...) and got the chance to be involved in all of them.

Trey Grainger

Author, AI-Powered Search

Trey Grainger is lead author of the book AI-Powered Search (Manning 2025) and founder of Searchkernel, a software consultancy building the next generation of AI-powered search. He also serves as a technical advisor at OpenSource Connections.


He previously served as CTO of Presearch, a decentralized web search engine, and as Chief Algorithms Officer and SVP of Engineering at Lucidworks, a search company whose technology powers hundreds of the world’s leading organizations. Trey is also co-author of the book Solr in Action (Manning 2014), as well as over a dozen other publications including books, journals, and research papers. Trey has 18 years of experience in search and data science focused on building self-learning search platforms integrating the most successful AI Search techniques.


Trey teaches AI Search in the course AI-Powered Search: Modern Retrieval for Humans & Agents with Doug Turnbull.

Previously at

Vespa.Ai
Reddit
Shopify.com
Searchkernel
Wikipedia
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