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Related Questions
- What are the key considerations for human evaluators when assessing the quality of automatically generated prompts for complex tasks?
- How does human evaluation help refine the performance of large language models in generating high-quality prompts?
- What are the potential biases that human evaluators may introduce when evaluating automatically generated prompts, and how can they be mitigated?
- Can you provide examples of successful applications of human evaluation in refining automatically generated prompts for complex tasks?
- What are the challenges of scaling human evaluation for large datasets and complex tasks, and how can they be addressed?
- How does human evaluation inform the development of more effective prompt engineering techniques for complex tasks?
- What are the benefits and limitations of using human evaluation in conjunction with other evaluation methods, such as automated metrics and self-supervised learning?
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