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Related Questions
- How do you ensure that the prompts are specific and unambiguous to improve the accuracy of the LLM's output?
- What are some common pitfalls to avoid when refining prompts, and how can they be addressed?
- Can you provide an example of how to refine a prompt through iterative testing and feedback loops?
- How can you measure the effectiveness of the refined prompts and determine if further refinement is needed?
- What role does active learning play in refining prompts for large language models, and how can it be incorporated into the process?
- How can you balance the trade-off between prompt specificity and generality to achieve optimal results from the LLM?
- What are some tools or techniques that can aid in the process of refining prompts, such as prompt engineering frameworks or prompt generation tools?
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