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Related Questions
- Can you explain how world knowledge is used to improve common sense in language models?
- How do language models like BERT and RoBERTa access and utilize world knowledge from large datasets?
- What are some specific techniques used in prompt engineering to incorporate world knowledge and improve common sense in language models?
- Can you provide examples of how world knowledge can be used to improve language understanding and generation in specific scenarios, such as understanding implied meaning or making inferences?
- How can world knowledge be represented and integrated into language model architectures to improve common sense and reasoning?
- What are some of the challenges and limitations of incorporating world knowledge through prompt engineering, and how can they be addressed?
- Can you describe how world knowledge can be used to improve language model performance in tasks such as question answering, text summarization, and conversational dialogue?
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