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Related Questions
- What is the role of prompt engineering in enhancing domain-knowledge transfer in large language models (LLMs)?
- How can prompt engineers optimize LLMs for domain-knowledge transfer to improve model performance and adaptability?
- What techniques can prompt engineers use to facilitate domain-knowledge transfer in LLMs, and what are their limitations?
- Can you provide examples of successful domain-knowledge transfer in LLMs, and what made them effective?
- How can prompt engineers balance the need for domain-specific knowledge with the risk of overfitting in LLMs?
- What is the relationship between domain-knowledge transfer and the concept of 'zero-shot' and 'few-shot' learning in LLMs?
- What role does meta-learning play in supporting domain-knowledge transfer in LLMs, and how can prompt engineers incorporate it into their strategies?
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