The availability of extended reality (XR) devices has widened their adoption, yet authoring interactive experiences remains complex for non-programmers. We introduce Tell-XR, an intelligent agent leveraging large language models (LLMs) to guide end-users in defining the interaction in XR settings using automations described as Event-Condition-Action (ECA) rules. Through a formative study, we identified the key conversation stages to define and refine automations, which informed the design of the system architecture. The evaluation study in two scenarios (a VR museum and an AR smart home) demonstrates the effectiveness of Tell-XR across different XR interaction settings.

Tell-XR: conversational end-user development of XR automations

Manca M.;Santoro C.;Simeoli L.;
2025

Abstract

The availability of extended reality (XR) devices has widened their adoption, yet authoring interactive experiences remains complex for non-programmers. We introduce Tell-XR, an intelligent agent leveraging large language models (LLMs) to guide end-users in defining the interaction in XR settings using automations described as Event-Condition-Action (ECA) rules. Through a formative study, we identified the key conversation stages to define and refine automations, which informed the design of the system architecture. The evaluation study in two scenarios (a VR museum and an AR smart home) demonstrates the effectiveness of Tell-XR across different XR interaction settings.
2025
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-032-04998-8
eXtended Reality, End-User Development, Immersive Authoring, Large Language Models, Meta Design, Rule
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/553542
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