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IllusionX: An LLM-powered mixed reality personal companion

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arxiv 2402.07924 v1 pith:ACYQ5MN7 submitted 2024-02-04 cs.HC cs.MM

Ramez Yousri , Zeyad Essam , Yehia Kareem , Youstina Sherief , Sherry Gamil , Soha Safwat This is my paper
classification cs.HCcs.MM
keywords usermixedrealitysystembettercompanionengagementfields
verification ladder T0 review T1 audit T2 compute T3 formal
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Mixed Reality (MR) and Artificial Intelligence (AI) are increasingly becoming integral parts of our daily lives. Their applications range in fields from healthcare to education to entertainment. MR has opened a new frontier for such fields as well as new methods of enhancing user engagement. In this paper, We propose a new system one that combines the power of Large Language Models (LLMs) and mixed reality (MR) to provide a personalized companion for educational purposes. We present an overview of its structure and components as well tests to measure its performance. We found that our system is better in generating coherent information, however it's rather limited by the documents provided to it. This interdisciplinary approach aims to provide a better user experience and enhance user engagement. The user can interact with the system through a custom-design smart watch, smart glasses and a mobile app.

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  1. Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR

    cs.LG 2025-06 conditional novelty 5.0 of 10

    The paper proposes M3T federated foundation models (FedFMs) as a privacy-preserving architecture for XR and codifies the key challenges as the SHIFT dimensions.

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