1Z0-1127-25 Fundamentals of Large Language Models Practice Question
A customer support company uses Cohere Command on OCI to answer user queries. They have enabled grounding with a knowledge base of product manuals. However, for about 20% of queries, the model provides incorrect product recommendations that are not in the manuals. The team has verified the knowledge base is up to date. What is the most likely cause and solution?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The query phrasing may not match the knowledge base; improve the retrieval system or use query rewriting.
The most likely cause is that the query phrasing does not align well with the knowledge base content, leading to retrieval of irrelevant or no documents. Even with an up-to-date knowledge base, if the query is phrased differently from the manual's text, grounding may fail to retrieve the correct information. Improving the retrieval system (e.g., using semantic search) or implementing query rewriting can bridge this gap, enabling the model to use the appropriate context and provide accurate recommendations. Option A might help if temperature were high, but the core issue is retrieval, not creativity. Option B (switching to a larger model) does not address the retrieval problem. Option D (increasing retrieved documents) could introduce more noise if the retrieved documents are already irrelevant.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model's temperature is too high, causing creative responses. Lower temperature to 0.
Why it's wrong here
Incorrect: Temperature control is not the primary cause; grounding is already enabled.
- ✗
The model is hallucinating; switch to a larger model.
Why it's wrong here
Incorrect: Larger models can still hallucinate if retrieval fails.
- ✓
The query phrasing may not match the knowledge base; improve the retrieval system or use query rewriting.
Why this is correct
Correct: Query mismatch causes retrieval of irrelevant content, leading to incorrect recommendations.
- ✗
The grounding settings are too restrictive; increase the number of retrieved documents.
Why it's wrong here
Incorrect: More documents may increase noise, not accuracy.
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