Title: Quiz 7 — Cross-Encoder Rerankers and Query Rewriting/Expansion
Course: AIINFRA 301: Production RAG & LLMOps — Observability and Evaluation > Section: Week 07 — Cross-Encoder Rerankers and Query Rewriting/Expansion

Q: What is the key architectural difference between a bi-encoder and a cross-encoder?
- Cross-encoders are always smaller models
- Bi-encoders encode query and document separately; cross-encoders score them jointly in one pass
- Bi-encoders can only handle short documents
- Cross-encoders don't use transformers
A: Bi-encoders encode query and document separately; cross-encoders score them jointly in one pass

Q: Because cross-encoders are more accurate than bi-encoders, production systems should use a cross-encoder to score every document in the corpus for every query.
- True
- False
A: False

Q: Approximately how much added latency does reranking \~50 candidates with cross-encoder/ms-marco-MiniLM-L-6-v2 typically add on CPU?
- 1-5ms
- 50-300ms
- 5-10 seconds
- 1-2 minutes
A: 50-300ms

Q: Name one hosted reranking alternative to self-hosting an open-source cross-encoder model.
Feedback: Sample/expected answer: Cohere Rerank

Q: In HyDE (Hypothetical Document Embeddings), what gets embedded and used for the search instead of the raw query?
- A summary of the document corpus
- A hypothetical answer to the query, generated by an LLM
- The query translated into another language
- A random sample of retrieved documents
A: A hypothetical answer to the query, generated by an LLM

Q: LangChain's MultiQueryRetriever guidance suggests that generating more query rewrites is always better, with no practical upper limit.
- True
- False
A: False

Q: According to the ordering discussed in this week's lecture (based on arXiv:2606.28367), once a strong cross-encoder reranker is already in place, which enhancement still yields a reliable additional gain?
Feedback: Sample/expected answer: Query expansion

Q: When a query has been rewritten or expanded (e.g., via HyDE or multi-query), which version of the query should the cross-encoder reranker use to score candidate relevance?
- The rewritten/expanded query, since it's a better search query
- Whichever version is longer
- The original user query
- An average embedding of all rewritten versions
A: The original user query