1Z0-1127-25 LLM Fundamentals Practice Question
When evaluating a summarization model, the team notices that the ROUGE-L score is high but human evaluators rate the summaries poorly for coherence. What does this discrepancy MOST likely indicate?
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
✓
ROUGE-L is not sensitive to coherence and fluency, only to n-gram overlap
ROUGE-L measures longest common subsequence overlap, focusing on word order recall. It does not capture coherence, factual consistency, or fluency. High ROUGE-L with low human scores suggests the summaries are lexically similar but not well-formed.
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 is suffering from hallucination
Why it's wrong here
Hallucination would likely reduce ROUGE-L because the generated text would differ from the reference.
- ✗
The reference summaries are too short
Why it's wrong here
Short reference summaries could inflate ROUGE-L but would not explain the coherence issue.
- ✓
ROUGE-L is not sensitive to coherence and fluency, only to n-gram overlap
Why this is correct
ROUGE-L measures longest common subsequence; it does not evaluate readability or logical flow.
- ✗
The human evaluators are biased
Why it's wrong here
While possible, it is more plausible that the metric fails to capture coherence.
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