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You have been tasked with fine-tuning a generative AI model for creating personalized content recommendations on a streaming platform. During testing, the model tends to recommend similar content repeatedly, which reduces user engagement. What approach should you take to enhance the diversity of recommendations while maintaining relevance?

You are training a Large Language Model (LLM) to generate customer service responses. During evaluation, you notice that the model is generating polite but factually incorrect responses to customer queries. Which approach should you take to address this issue?

Which metric is commonly used to evaluate machine-translation models?  

A retail company plans to deploy a generative AI model to automatically generate product descriptions for its e-commerce platform. What is the most important consideration to ensure that the generated descriptions are both engaging and factually accurate?

You are building a generative AI model to automate the creation of personalized financial reports for clients. You have trained two different models: Model A, a fine-tuned Large Language Model (LLM), and Model B, a transformer-based model trained from scratch. To decide which model to deploy, you need to evaluate them using relevant statistical performance metrics. Which of the following metrics and approaches would be most effective in comparing these models? (Select two)