Recent methods to bridge the semantic gap between knowledge graphs and natural language, such as joint graph-text embeddings, prompt-based schema alignment, and co-training frameworks, often require extensive tuning and are task-specific, lacking robust generalization, according to Peng et al. (2024).

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  Practices, opportunities and challenges in the fusion of knowledge ...

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

Referenced by nodes (2)

• knowledge graphs concept
• natural language concept