Answer / Sooraj Choudhary

Measuring diversity and coherence in text generated by Large Language Models (LLMs) can be challenging, but several methods exist. For diversity, techniques like BLEU, METEOR, and ROUGE evaluate the similarity between the model's output and a reference set of texts. To assess coherence, researchers often look at metrics such as semantic consistency, referential clarity, and topical relevance. These metrics can help ensure that the generated text is both diverse and coherent.

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