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Related Questions
- How do different evaluation metrics, such as perplexity and ROUGE, affect the interpretability of text generation models?
- In what ways do metrics like BLEU and METEOR influence the explainability of generated text?
- Can you explain how the choice of evaluation metric impacts the model's ability to generate coherent and contextually relevant text?
- What are the implications of using different evaluation metrics on the deployment of text generation models in real-world applications?
- How do metrics like fluency and grammaticality affect the explainability of generated text, and what are the implications for model deployment?
- Can you discuss the relationship between evaluation metrics and the model's ability to capture nuances of language, and how this impacts explainability?
- What are the potential consequences of using a single evaluation metric for text generation models, and how might this impact model deployment and explainability?
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