From Hallucinations to Truth: Strategies for Improving Chatbot Accuracy and Trustworthiness

Abstract

16 Corresponding author email : ouissem.touameur@gmail.com From Hallucinations to Truth: Strategies for Improving Chatbot Accuracy and Trustworthiness Ouissem, Touameur*; Harrag, Fouzi Farhat Abbas, Setif University Abstract Hallucinations in chatbot systems—instances where the model generates inaccurate or entirely fabricated information—pose a significant challenge to the reliability and trustworthiness of AI-driven communication. This paper provides a comprehensive review of the state-of-the-art in tackling hallucinations, detailing their underlying causes, varied manifestations, and the landscape of existing mitigation strategies. We critically examine leading approaches, including knowledge augmentation models, advanced fine-tuning methods, automated fact-checking systems, and the emerging role of explainable AI in identifying and reducing hallucinations