Phase 4: Advanced RAG · ~90 minutes · Python
Cross-Encoder Reranker
A bi-encoder embeds query and document independently. A cross-encoder concatenates them and reads both at once. The cross-encoder is the smartest reader and the slowest. Used as a second stage on the bi-encoder's top-k, it pays for itself.
Hiring signal: Can build cross-encoder reranker end to end
What you will learn
- Distinguish a bi-encoder retriever from a cross-encoder reranker by their input shape, parameter count, and per-query cost.
- Implement a small cross-encoder from scratch as a transformer block that consumes a packed (query, document) sequence and emits a single relevance scalar.
- Wire a two-stage retrieve-then-rerank pipeline: retrieve top-N with a cheap retriever, rerank N to top-K with the cross-encoder, return K.
- Measure the latency-vs-quality trade-off on a small fixture corpus and pick the right N for a given latency budget.
Introduction
Type: Build Languages: Python Prerequisites: Phase 11 lesson 06 (RAG), Phase 11 lesson 07 (advanced RAG); Phase 19 Track B foundations (lessons 20-29); Phase 19 lesson 65 (hybrid retrieval feeding this stage) Time: ~90 minutes
Objective
Learning objectives
- Distinguish a bi-encoder retriever from a cross-encoder reranker by their input shape, parameter count, and per-query cost.
- Implement a small cross-encoder from scratch as a transformer block that consumes a packed (query, document) sequence and emits a single relevance scalar.
- Wire a two-stage retrieve-then-rerank pipeline: retrieve top-N with a cheap retriever, rerank N to top-K with the cross-encoder, return K.
- Measure the latency-vs-quality trade-off on a small fixture corpus and pick the right N for a given latency budget.
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