Explain the Role of Re-Ranking in the Information Retrieval Process GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is a characteristic of learning-to-rank models used in re-ranking?

   • AThey are used to compress the index to reduce storage
   • BThey are trained to predict the relevance score of a document for a given query
   • CThey are used to generate embeddings for the entire corpus during indexing
   • DThey are rule-based systems that do not require training data
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2. 2expert · hard

   A search system currently retrieves 50 documents per query and re-ranks them with a cross-encoder. The team wants to improve the recall of the system, but they are concerned that increasing the candidate set will increase latency. They have a fixed latency budget. What is the best way to improve recall without exceeding the latency budget?

   • AUse a bi-encoder for re-ranking to reduce latency and allow a larger candidate set.
   • BRemove the re-ranking stage and rely on the initial retrieval order.
   • CKeep the candidate set at 50 but use a larger cross-encoder to improve accuracy.
   • DIncrease the candidate set to 100 and use a smaller, faster cross-encoder for re-ranking.
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4. 3application · medium

   A company's search system currently retrieves 100 documents per query and then re-ranks all of them with a cross-encoder. The system is experiencing high latency, and users are complaining about slow response times. The team wants to maintain the quality of the top results while reducing latency. What is the most effective approach?

   • AIncrease the number of candidates to 200 to improve recall before re-ranking.
   • BReduce the number of candidates passed to the re-ranker to the top 20.
   • CUse a larger cross-encoder model to improve accuracy.
   • DRemove the re-ranking stage entirely and rely on the initial retrieval order.
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5. 4foundation · easy

   What is the primary impact of re-ranking on the quality of retrieved results?

   • AIt reduces the total number of documents stored in the index
   • BIt increases the number of documents retrieved from the index
   • CIt makes the initial retrieval stage unnecessary
   • DIt improves the relevance of the top results by reordering the candidate set
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6. 5foundation · easy

   What is the primary objective of the initial retrieval stage in a retrieval system?

   • AMaximize recall by retrieving a broad set of potentially relevant documents
   • BMinimize the number of documents retrieved to reduce processing time
   • CMaximize precision by returning only the most relevant documents
   • DRank documents using a complex cross-encoder model
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