Our Paper ?QoEXplainer: Mediating Explainable Quality of Experience Models with Large Language Models“ was presented at the 16th International Conference on Quality of Multimedia Experience (QoMEX). The paper introduces QoEXplainer, a dashboard that uses large language models and mediator usage to illustrate explainable, data-driven Quality of Experience (QoE) models to help users understand the model relationships through an interactive chatbot interface.

Abstract:

In this paper, we present QoEXplainer, a QoE dashboard for supporting humans in understanding the internals of an explainable, data-driven Quality of Experience model. This tool leverages Large Language Models and the concept of Mediators to convey relevant explanations to the user in an understandable, chatbot-like fashion. For this purpose, our tool QoEXplainer integrates a data-driven video streaming QoE model and techniques from Explainable Artificial Intelligence. The resulting data-driven model explanations are illustrated in the dashboard and users can interact with the chatbot to ask questions about the data and QoE model and control the dashboard to enhance model understanding. With this hybrid demo, we aim to conduct a live study at QoMEX 2024 to evaluate Mediators in the context of (data-driven) QoE modelling with domain experts.