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Nodes2024

Dev Conference by Neo4j

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Enhance LLM Applications’ Trustworthiness and Explainability

Session Track: AI

Session Time:

Session description

Knowledge graphs improve information retrieval in LLM-based systems by providing richer contexts for better answers and linking data to generate more relevant responses. In this talk, we will explore how integrating knowledge graphs with LLM applications enhances their trustworthiness and explainability. They offer transparent information paths, increasing precision and allowing users to see reliable information sources. Applicable across various fields, knowledge graphs improve the quality of information retrieval, enabling LLMs to generate accurate and contextually relevant responses.

Speaker

photo of Leann Chen

Leann Chen

Generative AI Developer Advocate, Diffbot

Leann is a Generative AI Developer Advocate at Diffbot, who currently focuses on enhancing the performance of LLM-based applications by integrating the strengths of knowledge graphs. She creates content about Generative AI and Knowledge Graph Content on YouTube and LinkedIn.