From Hallucinations to Grounded Responses: Building RAG Systems That Actually Know Your Business

Authors

  • Amaan Javed

Keywords:

Retrieval-Augmented Generation, Hallucination Detection, Dense Passage Retrieval, Document Chunking, Knowledge Synchronization

Abstract

Large language models have transformed enterprise applications, but the issue of hallucination is animportant obstacle to their use in domain-specific applications where accuracy is most important.Retrieval-Augmented Generation is now the most popular setup that separates where knowledge is stored from how it is created, allowing for updates

References

Ziwei Ji et al., "Survey of Hallucination in Natural Language Generation," arXiv:2202.03629, 2024. [Online]. Available: https://arxiv.org/abs/2202.03629

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Published

2026-02-17

How to Cite

Amaan Javed. (2026). From Hallucinations to Grounded Responses: Building RAG Systems That Actually Know Your Business. Journal of Computational Analysis and Applications (JoCAAA), 35(2), 315–322. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4948

Issue

Vol. 35 No. 2 (2026): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.