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Related Questions
- How can researchers avoid making overly simplistic assumptions about user behavior and preferences in large language model design?
- What are some common pitfalls of oversimplifying the complexities of human language and cognition in large language model development?
- What strategies can be employed to ensure that large language models are designed with a nuanced understanding of human communication and context?
- How can designers balance the need for simplicity and ease of use with the need for accuracy and depth in large language model functionality?
- What role do assumptions play in shaping the performance and limitations of large language models, and how can they be identified and addressed?
- What are some best practices for testing and validating the assumptions underlying large language model design decisions?
- How can the development of large language models be made more transparent and accountable to ensure that assumptions are clearly articulated and tested?
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