ROUGE
A recall-oriented metric that compares generated summaries to reference text by overlap.
ROUGE (Recall-Oriented Understudy for Gisting Evaluation) measures how much of a human-written reference summary is captured by a machine-generated output. The most common variants are ROUGE-N, which counts overlapping n-grams, and ROUGE-L, which finds the longest common subsequence. Because ROUGE emphasizes recall, it rewards outputs that cover the key ideas in the reference, making it well-suited for summarization tasks.
The key exam distinction is ROUGE versus BLEU: BLEU is precision-oriented and designed for translation, while ROUGE is recall-oriented and designed for summarization. On AIF-C01, expect questions asking which metric to use when evaluating a summarization model in Amazon Bedrock or Amazon SageMaker — ROUGE is the standard answer for that scenario.
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