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MLA-C02 practice question: RAG architecture and retrieval tuning (2 of 2)

ML Model and Foundation Model (FM) Development A free question from our original MLA-C02 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A pet insurer built a retrieval-augmented assistant over 40,000 policy clauses in an Amazon Bedrock knowledge base. For questions about exclusions, the top five retrieved clauses are often topically similar but do not answer the question, and the answers are wrong.

The retrieved set must be reordered so that the clauses that actually answer the question come first. Latency must stay under three seconds for each answer, and the team does not want to change the embedding model or re-index the clauses.

Which change best meets these requirements?

Choose one answer.

  1. A. Add a reranking model to the retrieval step so that it scores the retrieved clauses against the question and returns them in that order.
  2. B. Increase the number of results returned from the vector search to 100, and pass all of them to the foundation model together with the customer's question.
  3. C. Re-index all 40,000 clauses with a larger chunk size, so that each chunk holds an entire policy section.
  4. D. Replace the foundation model that writes answers with a larger one, expecting it to ignore unrelated clauses.
Show the answer and explanation

Answer: A

  • A. Right: Correct. A reranking model rescores the candidates by relevance to the question, so answering clauses move to the top. The embeddings and index stay unchanged, and only a small number of passages is passed on. Learn more: Improve the relevance of query responses with a reranker model (opens in a new tab)
  • B. Wrong: Passing 100 clauses increases the model input and can push latency past the target, and the relevant clause may still sit low in the list. The stem asks for better ordering, not more text.
  • C. Wrong: Re-indexing is the change the team wants to avoid, and larger chunks do not reorder the candidates. Each section also brings more irrelevant text into the answer.
  • D. Wrong: The generation model is not the step that orders the clauses, and a bigger model adds cost and latency. The wrong clauses are reaching the model in the first place.

Explanation

A reranking model reorders a set of retrieved passages by relevance to the question, which fixes the case where the right clause ranks low. This needs no re-indexing and keeps the model input small. Larger result sets, bigger chunks or a larger generator each add cost or text without solving the ordering problem.

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