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Related Questions
- How does domain knowledge impact the performance of large language models on out-of-domain prompts?
- What are some strategies for leveraging domain knowledge to improve model performance on ambiguous prompts?
- Can you provide examples of how domain knowledge can be incorporated into prompt engineering to handle out-of-domain or ambiguous prompts?
- How does the type of domain knowledge (e.g. linguistic, ontological, or task-specific) affect the handling of out-of-domain or ambiguous prompts?
- Are there any trade-offs between incorporating domain knowledge and maintaining model flexibility and adaptability?
- Can you discuss the role of meta-learning and few-shot learning in leveraging domain knowledge for out-of-domain or ambiguous prompts?
- How can domain knowledge be used to improve the robustness and reliability of language models in real-world applications?
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