Publications

@inproceedings{mereu_using_2025,

title = {Using LLMs to enhance end-user development support in XR},

author = {J. Mereu},

editor = {Paneva V. and Tetteroo D. and Frau V. and Feger S. and Spano D. and Paterno F. and Sauer S. and Manca M.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105008755984&partnerID=40&md5=bfaaa38c3bee309621426f8f35332107},

isbn = {16130073 (ISSN)},

year  = {2025},

date = {2025-01-01},

booktitle = {CEUR Workshop Proc.},

volume = {3978},

publisher = {CEUR-WS},

abstract = {This paper outlines the center stage of my PhD research, which aims to empower non-developer users to create and customize eXtended Reality (XR) environments through End-User Development (EUD) techniques combined with the latest AI tools. In particular, I describe my contributions to the EUD4XR project, detailing both the work completed and the ongoing developments. EUD4XR seeks to support end-users in customizing XR content with the assistance of a Large Language Model (LLM)-based conversational agent. © 2025 Copyright for this paper by its authors.},

keywords = {Artificial intelligence, Condition, Configuration, Development support, Development technique, End-User Development, End-Users, Event-condition-action, Event-Condition-Actions, Extended reality, Human computer interaction, Information Systems, Information use, Natural Language, Natural language processing systems, Natural languages, Rule, rules},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{carcangiu_conversational_2025,

title = {Conversational Rule Creation in XR: User’s Strategies in VR and AR Automation},

author = {A. Carcangiu and M. Manca and J. Mereu and C. Santoro and L. Simeoli and L. D. Spano},

editor = {Santoro C. and Schmidt A. and Matera M. and Bellucci A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009012634&doi=10.1007%2f978-3-031-95452-8_4&partnerID=40&md5=67e2b8ca4bb2b508cd41548e3471705b},

doi = {10.1007/978-3-031-95452-8_4},

isbn = {03029743 (ISSN); 978-303195451-1 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15713 LNCS},

pages = {59–79},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {Rule-based approaches allow users to customize XR environments. However, the current menu-based interfaces still create barriers for end-user developers. Chatbots based on Large Language Models (LLMs) have the potential to reduce the threshold needed for rule creation, but how users articulate their intentions through conversation remains under-explored. This work investigates how users express event-condition-action automation rules in Virtual Reality (VR) and Augmented Reality (AR) environments. Through two user studies, we show that the dialogues share consistent strategies across the interaction setting (keywords, difficulties in expressing conditions, task success), even if we registered different adaptations for each setting (verbal structure, event vs action first rules). Our findings are relevant for the design and implementation of chatbot-based support for expressing automations in an XR setting. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},

keywords = {'current, Automation, Chatbots, Condition, End-User Development, Extended reality, Human computer interaction, Immersive authoring, Language Model, Large language model, large language models, Rule, Rule-based approach, rules, User interfaces},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{artizzu_end-user_2024,

title = {End-User Development for eXtended Reality using a multimodal Intelligent Conversational Agent},

author = {V. Artizzu and A. Carcangiu and M. Manca and A. Mattioli and J. Mereu and F. Paternò and C. Santoro and L. Simeoli and L. D. Spano},

editor = {Wang N. and Bellucci A. and Anthes C. and Daeijavad P. and Friedl-Knirsch J. and Maurer F. and Pointecker F. and Spano L.D.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196077262&partnerID=40&md5=3d5f022f30a1f0e3e5e81133d07823b5},

isbn = {16130073 (ISSN)},

year  = {2024},

date = {2024-01-01},

booktitle = {CEUR Workshop Proc.},

volume = {3704},

publisher = {CEUR-WS},

abstract = {In the past years, both the research community and commercial products have proposed various solutions aiming to support end-user developers (EUDevs), namely users without extensive programming skills, to build and customize XR experiences. However, current tools may not fully eliminate the potential for user errors or misunderstandings. In this paper, we present EUD4XR, a methodology consisting of an intelligent conversational agent to provide contextual help, to EUDevs, during the authoring process. The key characteristics of this agent are its multimodality, comprehending the user’s voice, gaze, and pointing, combined with the environment status. Moreover, the agent could also demonstrate concepts, suggest components, and help explain errors further to reduce misunderstandings for end-user developers of VR/XR. © 2024 Copyright for this paper by its authors.},

keywords = {Condition, Context, End-User Development, Event-condition-action, Extended reality, Immersive authoring, Language Model, Large language model, Meta-design, multimodal input, Multimodal inputs, Rule, rules, User interfaces},

pubstate = {published},

tppubtype = {inproceedings}

}