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Related Questions
- How do knowledge graph embeddings help LLMs represent complex relationships between entities?
- Can you explain the difference between knowledge graph embeddings and traditional word embeddings in LLMs?
- How do knowledge graph embeddings enable LLMs to capture abstract concepts such as emotions and intentions?
- What are some common applications of knowledge graph embeddings in LLMs for real-world tasks?
- How do knowledge graph embeddings improve the performance of LLMs in tasks such as question answering and text classification?
- What are some challenges in using knowledge graph embeddings in LLMs, and how can they be addressed?
- Can you provide examples of how knowledge graph embeddings have been used in LLMs to capture relationships between entities in specific domains, such as medicine or finance?
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