# Generative AI-Based Virtual Assistant Using Retrieval-Augmented Generation: An evaluation study for bachelor projects (BNAIC/BeNeLearn 2024)

> This paper develops a Retrieval-Augmented Generation virtual assistant to help Maastricht University students navigate project regulations, improving accuracy and reliability in specialized educational contexts using Large Language Models.

Published: 2025-03-14
Source: https://www.edudacs.nl/publications/67d447b5bdeb32ea915ff0fa

**Abstract**: Large Language Models have been increasingly employed in the creation of Virtual Assistants due to their ability to generate human-like text and handle complex inquiries. While these models hold great promise, challenges such as hallucinations, missing information, and the difficulty of providing accurate and context-specific responses persist, particularly when applied to highly specialized content domains. In this paper, we focus on addressing these challenges by developing a virtual assistant designed to support students at Maastricht University in navigating project-specific regulations. We propose a virtual assistant based on a Retrieval-Augmented Generation system that enhances the accuracy and reliability of responses by integrating up-to-date, domain specific knowledge. Through a robust evaluation framework and real-life testing, we demonstrate that our virtual assistant can effectively meet the needs of students while addressing the inherent challenges of applying Large Language Models to a specialized educational context. This work contributes to the ongoing discourse on improving LLM-based systems for specific applications and highlights areas for further research. 

[https://youtu.be/jXC7-cPD4Z4?si=fgBvfTeth9PCYYoC](https://youtu.be/jXC7-cPD4Z4?si=fgBvfTeth9PCYYoC)

**Authors**: Dumitru Versebeniuc, Martijn Elands, Sara Falahatkar, Chiara Magrone, Mohammad Falah, Martijn Bousse and Aki Harma

**Conference**: BNAIC/BeNeLearn 2024, Utrecht.

**Link**: [https://bnaic2024.sites.uu.nl/wp-content/uploads/sites/986/2024/10/Generative-AI-based-Virtual-Assistant-using-Retrieval-Augmented-Generation-An-evaluation-study-for-bachelor-projects.pdf](https://bnaic2024.sites.uu.nl/wp-content/uploads/sites/986/2024/10/Generative-AI-based-Virtual-Assistant-using-Retrieval-Augmented-Generation-An-evaluation-study-for-bachelor-projects.pdf)