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Related Questions
- What are some common pitfalls in designing LLM prompts that can lead to simplistic or lacking explanations?
- How do LLMs' limitations in handling complex contextual dependencies contribute to oversimplification of explanations?
- What are some strategies for mitigating the risk of LLMs generating explanations that lack nuance?
- Can you provide examples of how LLMs can be trained to recognize and address their own limitations in generating explanations?
- What role do you think data quality plays in the accuracy and nuance of LLM-generated explanations?
- How do you think the lack of common sense or real-world experience in LLMs affects their ability to generate nuanced explanations?
- What are some potential consequences of relying on LLMs to generate explanations in high-stakes domains, such as healthcare or finance?
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