1Z0-1127-25 LLM Fundamentals Practice Question
A data scientist is evaluating an LLM for a summarization task. They have a set of human-written reference summaries. Which THREE metrics are commonly used to evaluate summarization quality? (Choose three.)
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
✓
BLEU
ROUGE, BLEU, and BERTScore are all used for summarization evaluation. Perplexity measures model confidence, and cosine similarity is for embedding comparison.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
BLEU
Why this is correct
BLEU is precision-oriented and often used alongside ROUGE.
- ✗
Cosine similarity
Why it's wrong here
Cosine similarity is not a standard summarization metric; it is used for embedding similarity.
- ✗
Perplexity
Why it's wrong here
Perplexity is not a summarization metric; it measures language model fluency.
- ✓
BERTScore
Why this is correct
BERTScore uses embeddings to measure semantic similarity.
- ✓
ROUGE
Why this is correct
ROUGE is recall-oriented and standard for summarization.
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