Answer / Vishal Deep

Various metrics are used to evaluate the quality of generative outputs from Large Language Models (LLMs). Automatic evaluation metrics like BLEU, METEOR, and ROUGE focus on measuring the similarity between the model's output and a reference set of texts. Human-rated evaluations provide a more nuanced assessment of factors such as fluency, grammatical correctness, coherence, and relevance. Hybrid approaches that combine both automatic and human evaluations can offer a comprehensive understanding of the model's performance.

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How do foundation models support Generative AI systems?

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