Knowledge graph-enhanced large language models often incur high computational overhead due to the necessity of graph traversal, entity linking, and dynamic retrieval during inference, which introduces latency that hinders deployment in real-time applications like dialogue systems, autonomous agents, and online recommendation.

Authors

• Person: Not available Organization: Frontiers
  Practices, opportunities and challenges in the fusion of knowledge ...

Sources

• Practices, opportunities and challenges in the fusion of knowledge ... www.frontiersin.org Frontiers via serper

Referenced by nodes (4)

• entity linking concept
• Knowledge graph-enhanced large language models concept
• autonomous agents concept
• graph traversal concept