PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #340: Real Exam Question with Answer & Explanation

Question

You deployed a conversational application that uses a large language model (LLM). The application has 1,000 users. You collect user feedback about the verbosity and accuracy of the model 's responses. The user feedback indicates that the responses are factually correct but users want different levels of verbosity depending on the type of question. You want the model to return responses that are more consistent with users' expectations, and you want to use a scalable solution. What should you do?

Options

• AImplement a keyword-based routing layer. If the user's input contains the words "detailed" or
• BAsk users to provide examples of responses with the appropriate verbosity as a list of question
• CAsk users to indicate all scenarios where they expect concise responses versus verbose
• DExperiment with other proprietary and open-source LLMs. Perform A/B testing by setting each