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Related Questions
- What are some scenarios where prompt priming is more effective than data augmentation for improving LLM performance?
- Can you give examples of how prompt priming can help improve LLM performance in tasks that require contextual understanding?
- In what situations would you recommend using prompt priming over data augmentation to fine-tune LLMs?
- How does prompt priming compare to data augmentation in terms of improving LLM performance for tasks that require common sense knowledge?
- Can you provide examples of how prompt priming can help improve LLM performance in tasks that require creativity and generation?
- What are some common pitfalls to avoid when using prompt priming to improve LLM performance, and how does it differ from data augmentation?
- How can prompt priming be used to improve LLM performance in tasks that require domain-specific knowledge and terminology?
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