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Related Questions
- What are some key considerations for adapting language models to generate explanations that are culturally sensitive?
- How can prompt engineers use cultural context to improve the accuracy and relevance of generated explanations?
- What are some strategies for incorporating diverse perspectives and values into the training data for language models?
- Can you provide examples of culturally-specific language and idioms that can be used to generate explanations that resonate with different audiences?
- How can prompt engineers use linguistic and cultural nuances to avoid generating explanations that are insensitive or offensive?
- What role do cultural context and background knowledge play in generating explanations that are relevant and relatable to specific cultural groups?
- Can you describe some best practices for testing and validating the cultural sensitivity of generated explanations?
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