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Related Questions
- What are some common challenges in integrating knowledge graph embeddings into large language models (LLMs)?
- How can the issue of high computational complexity when training knowledge graph embeddings be addressed?
- What is the impact of knowledge graph sparsity on the performance of LLMs, and how can it be mitigated?
- How do knowledge graph embeddings handle missing relationships between entities, and what are the implications for LLMs?
- What are some strategies for reducing the dimensionality of knowledge graph embeddings without compromising their effectiveness?
- How can the issue of knowledge graph drift, where the graph becomes outdated, be addressed in LLMs?
- What are some methods for leveraging multi-modal knowledge graphs, which combine text, images, and other data, in LLMs?
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