Improving LLM Accuracy through Entity-Aware Knowledge Graph  Grounding in Distributed Conversational AI Systems

Saradha Nagarajan, Jeet Mehta, Chirag Agarwal

Improving LLM Accuracy through Entity-Aware Knowledge Graph Grounding in Distributed Conversational AI Systems

Authors

Saradha Nagarajan, Jeet Mehta, Chirag Agarwal

Keywords:

Large language models; Entity-aware grounding; Knowledge graphs; Distributed conversational AI; Hallucination reduction

Abstract

Large language models (LLMs) are increasingly deployed in distributed conversational AIsystems; however, their practical adoption is often constrained by issues of factual inaccuracy,hallucination, and inconsistent entity handling across multi-agent interactions. This study investigates an entity-aware

References

Agarwal, K., Khare, O., Sharma, A., Prakash, A., & Shukla, A. K. (2024). Artificial Intelligence in a Distributed System of the Future. Decentralized Systems and Distributed Computing, 317-335

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Published

2024-11-20

How to Cite

Saradha Nagarajan, Jeet Mehta, Chirag Agarwal. (2024). Improving LLM Accuracy through Entity-Aware Knowledge Graph Grounding in Distributed Conversational AI Systems . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2794–2807. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4479