Current research addresses the gap between temporal knowledge graphs and large language models through retrieval-augmented generation frameworks, such as GenTKG (Liao et al., 2024), and by integrating few-shot learning and instruction tuning to reduce computational costs.

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)

• Retrieval-Augmented Generation (RAG) concept
• few-shot learning concept
• temporal knowledge graphs concept
• instruction tuning concept