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Detecting and Mitigating Hallucinations in Large Language Models: A Comparative Study of Generative and Transformer-Based Approaches

Rupinder Kaur Sangeetha Kaithakkadu Thankachan
· 0 citations · 11 references

TL;DR

The results suggest that no single architecture guarantees factual reliability, however, contextual grounding and verification mechanisms can significantly improve response quality and highlight the importance of combining language modelling capabilities with grounding strategies to support the development of more reliable AI systems.

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