AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2025
Zhang, H.; Zha, S.; Cai, J.; Wohn, D. Y.; Carroll, J. M.
Generative AI in Virtual Reality Communities: A Preliminary Analysis of the VRChat Discord Community Proceedings Article
In: Conf Hum Fact Comput Syst Proc, Association for Computing Machinery, 2025, ISBN: 979-840071395-8 (ISBN).
Abstract | Links | BibTeX | Tags: AI assistant, AI Technologies, Coding framework, Ethical technology, Human-ai collaboration, Immersive, On-line communities, online community, Preliminary analysis, Property, Qualitative analysis, user experience, Users' experiences
@inproceedings{zhang_generative_2025,
title = {Generative AI in Virtual Reality Communities: A Preliminary Analysis of the VRChat Discord Community},
author = {H. Zhang and S. Zha and J. Cai and D. Y. Wohn and J. M. Carroll},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005770564&doi=10.1145%2f3706599.3720120&partnerID=40&md5=9bdfc4e70b9b361d67791932f5a56413},
doi = {10.1145/3706599.3720120},
isbn = {979-840071395-8 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Conf Hum Fact Comput Syst Proc},
publisher = {Association for Computing Machinery},
abstract = {As immersive social platforms like VRChat increasingly adopt generative AI (GenAI) technologies, it becomes critical to understand how community members perceive, negotiate, and utilize these tools. In this preliminary study, we conducted a qualitative analysis of VRChat-related Discord discussions, employing a deductive coding framework to identify key themes related to AI-assisted content creation, intellectual property disputes, and evolving community norms. Our findings offer preliminary insights into the complex interplay between the community’s enthusiasm for AI-driven creativity and deep-rooted ethical and legal concerns. Users weigh issues of fair use, data ethics, intellectual property, and the role of community governance in establishing trust. By highlighting the tensions and trade-offs as users embrace new creative opportunities while seeking transparency, fair attribution, and equitable policies, this research offers valuable insights for designers, platform administrators, and policymakers aiming to foster responsible, inclusive, and ethically sound AI integration in future immersive virtual environments. © 2025 Copyright held by the owner/author(s).},
keywords = {AI assistant, AI Technologies, Coding framework, Ethical technology, Human-ai collaboration, Immersive, On-line communities, online community, Preliminary analysis, Property, Qualitative analysis, user experience, Users' experiences},
pubstate = {published},
tppubtype = {inproceedings}
}
As immersive social platforms like VRChat increasingly adopt generative AI (GenAI) technologies, it becomes critical to understand how community members perceive, negotiate, and utilize these tools. In this preliminary study, we conducted a qualitative analysis of VRChat-related Discord discussions, employing a deductive coding framework to identify key themes related to AI-assisted content creation, intellectual property disputes, and evolving community norms. Our findings offer preliminary insights into the complex interplay between the community’s enthusiasm for AI-driven creativity and deep-rooted ethical and legal concerns. Users weigh issues of fair use, data ethics, intellectual property, and the role of community governance in establishing trust. By highlighting the tensions and trade-offs as users embrace new creative opportunities while seeking transparency, fair attribution, and equitable policies, this research offers valuable insights for designers, platform administrators, and policymakers aiming to foster responsible, inclusive, and ethically sound AI integration in future immersive virtual environments. © 2025 Copyright held by the owner/author(s).
2024
Haramina, E.; Paladin, M.; Petričušić, Z.; Posarić, F.; Drobnjak, A.; Botički, I.
Learning Algorithms Concepts in a Virtual Reality Escape Room Proceedings Article
In: S., Babic; Z., Car; M., Cicin-Sain; D., Cisic; P., Ergovic; T.G., Grbac; V., Gradisnik; S., Gros; A., Jokic; A., Jovic; D., Jurekovic; T., Katulic; M., Koricic; V., Mornar; J., Petrovic; K., Skala; D., Skvorc; V., Sruk; M., Svaco; E., Tijan; N., Vrcek; B., Vrdoljak (Ed.): ICT Electron. Conv., MIPRO - Proc., pp. 2057–2062, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835038249-5 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Computational complexity, Computer generated three dimensional environment, E-Learning, Education, Escape room, Extended reality, generative artificial intelligence, Learn+, Learning, Learning algorithms, Learning systems, Puzzle, puzzles, user experience, User study, User testing, Users' experiences, Virtual Reality
@inproceedings{haramina_learning_2024,
title = {Learning Algorithms Concepts in a Virtual Reality Escape Room},
author = {E. Haramina and M. Paladin and Z. Petričušić and F. Posarić and A. Drobnjak and I. Botički},
editor = {Babic S. and Car Z. and Cicin-Sain M. and Cisic D. and Ergovic P. and Grbac T.G. and Gradisnik V. and Gros S. and Jokic A. and Jovic A. and Jurekovic D. and Katulic T. and Koricic M. and Mornar V. and Petrovic J. and Skala K. and Skvorc D. and Sruk V. and Svaco M. and Tijan E. and Vrcek N. and Vrdoljak B.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198221737&doi=10.1109%2fMIPRO60963.2024.10569447&partnerID=40&md5=8a94d92d989d1f0feb84eba890945de8},
doi = {10.1109/MIPRO60963.2024.10569447},
isbn = {979-835038249-5 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {ICT Electron. Conv., MIPRO - Proc.},
pages = {2057–2062},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Although the standard way to learn algorithms is by coding, learning through games is another way to obtain knowledge while having fun. Virtual reality is a computer-generated three-dimensional environment in which the player is fully immersed by having external stimuli mostly blocked out. In the game presented in this paper, players are enhancing their algorithms skills by playing an escape room game. The goal is to complete the room within the designated time by solving puzzles. The puzzles change for every playthrough with the use of generative artificial intelligence to provide every player with a unique experience. There are multiple types of puzzles such as. time complexity, sorting algorithms, searching algorithms, and code execution. The paper presents the results of a study indicating students' preference for learning through gaming as a method of acquiring algorithms knowledge. © 2024 IEEE.},
keywords = {Artificial intelligence, Computational complexity, Computer generated three dimensional environment, E-Learning, Education, Escape room, Extended reality, generative artificial intelligence, Learn+, Learning, Learning algorithms, Learning systems, Puzzle, puzzles, user experience, User study, User testing, Users' experiences, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Although the standard way to learn algorithms is by coding, learning through games is another way to obtain knowledge while having fun. Virtual reality is a computer-generated three-dimensional environment in which the player is fully immersed by having external stimuli mostly blocked out. In the game presented in this paper, players are enhancing their algorithms skills by playing an escape room game. The goal is to complete the room within the designated time by solving puzzles. The puzzles change for every playthrough with the use of generative artificial intelligence to provide every player with a unique experience. There are multiple types of puzzles such as. time complexity, sorting algorithms, searching algorithms, and code execution. The paper presents the results of a study indicating students' preference for learning through gaming as a method of acquiring algorithms knowledge. © 2024 IEEE.
Bayat, R.; Maio, E. De; Fiorenza, J.; Migliorini, M.; Lamberti, F.
Exploring Methodologies to Create a Unified VR User-Experience in the Field of Virtual Museum Experiences Proceedings Article
In: IEEE Gaming, Entertain., Media Conf., GEM, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835037453-7 (ISBN).
Abstract | Links | BibTeX | Tags: Cultural heritages, Meta-museum, Meta-museums, Metaverse, Metaverses, Research frontiers, Research opportunities, user experience, User experience design, User interfaces, User-Experience Design, Users' experiences, Virtual avatar, Virtual machine, Virtual museum, Virtual Reality, Virtual reality experiences
@inproceedings{bayat_exploring_2024,
title = {Exploring Methodologies to Create a Unified VR User-Experience in the Field of Virtual Museum Experiences},
author = {R. Bayat and E. De Maio and J. Fiorenza and M. Migliorini and F. Lamberti},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199517817&doi=10.1109%2fGEM61861.2024.10585452&partnerID=40&md5=203c7b426a11144acc7a2fedbbac6a98},
doi = {10.1109/GEM61861.2024.10585452},
isbn = {979-835037453-7 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {IEEE Gaming, Entertain., Media Conf., GEM},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The emergence of Virtual Reality (VR) and meta-verse have opened doors to new research opportunities and frontiers in User Experience (UX). Within the cultural heritage domain, one of the key concepts is that of the Virtual Museums (VMs), whose definition has been extended through time by many research works and applications. However, most of the studies performed so far focused on only one application, and studied its UX without taking into account the experience with other VR experiences possibly available in the VM. The purpose of this work is to give a contribution for an optimal design to create a unified UX across multiple VR experiences. More specifically, the research included the development of two applications, respectively a VM in a metaverse platform and a virtual learning workshop as an individual application. With this premise, the study will also consider two fundamental elements for an effective UX design: a Virtual Environment (VE) and an Intelligent Virtual Avatar (IVA). In particular, the latest was developed following current trends about generative AI, integrating an IVA powered by a Large Language Model (LLM). © 2024 IEEE.},
keywords = {Cultural heritages, Meta-museum, Meta-museums, Metaverse, Metaverses, Research frontiers, Research opportunities, user experience, User experience design, User interfaces, User-Experience Design, Users' experiences, Virtual avatar, Virtual machine, Virtual museum, Virtual Reality, Virtual reality experiences},
pubstate = {published},
tppubtype = {inproceedings}
}
The emergence of Virtual Reality (VR) and meta-verse have opened doors to new research opportunities and frontiers in User Experience (UX). Within the cultural heritage domain, one of the key concepts is that of the Virtual Museums (VMs), whose definition has been extended through time by many research works and applications. However, most of the studies performed so far focused on only one application, and studied its UX without taking into account the experience with other VR experiences possibly available in the VM. The purpose of this work is to give a contribution for an optimal design to create a unified UX across multiple VR experiences. More specifically, the research included the development of two applications, respectively a VM in a metaverse platform and a virtual learning workshop as an individual application. With this premise, the study will also consider two fundamental elements for an effective UX design: a Virtual Environment (VE) and an Intelligent Virtual Avatar (IVA). In particular, the latest was developed following current trends about generative AI, integrating an IVA powered by a Large Language Model (LLM). © 2024 IEEE.
Min, Y.; Jeong, J. -W.
Public Speaking Q&A Practice with LLM-Generated Personas in Virtual Reality Proceedings Article
In: U., Eck; M., Sra; J., Stefanucci; M., Sugimoto; M., Tatzgern; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 493–496, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833150691-9 (ISBN).
Abstract | Links | BibTeX | Tags: Digital elevation model, Economic and social effects, Language Model, Large language model-based persona generation, LLM-based Persona Generation, Model-based OPC, Personnel training, Power, Practice systems, Presentation Anxiety, Public speaking, Q&A practice, user experience, Users' experiences, Virtual environments, Virtual Reality, VR training
@inproceedings{min_public_2024,
title = {Public Speaking Q&A Practice with LLM-Generated Personas in Virtual Reality},
author = {Y. Min and J. -W. Jeong},
editor = {Eck U. and Sra M. and Stefanucci J. and Sugimoto M. and Tatzgern M. and Williams I.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214393734&doi=10.1109%2fISMAR-Adjunct64951.2024.00143&partnerID=40&md5=992d9599bde26f9d57d549639869d124},
doi = {10.1109/ISMAR-Adjunct64951.2024.00143},
isbn = {979-833150691-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},
pages = {493–496},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This paper introduces a novel VR-based Q&A practice system that harnesses the power of Large Language Models (LLMs). We support Q&A practice for upcoming public speaking by providing an immersive VR training environment populated with LLM-generated audiences, each capable of posing diverse and realistic questions based on different personas. We conducted a pilot user study involving 20 participants who engaged in VR-based Q&A practice sessions. The sessions featured a variety of questions regarding presentation material provided by the participants, all of which were generated by LLM-based personas. Through post-surveys and interviews, we evaluated the effectiveness of the proposed method. The participants valued the system for engagement and focus while also identifying several areas for improvement. Our study demonstrated the potential of integrating VR and LLMs to create a powerful, immersive tool for Q&A practice. © 2024 IEEE.},
keywords = {Digital elevation model, Economic and social effects, Language Model, Large language model-based persona generation, LLM-based Persona Generation, Model-based OPC, Personnel training, Power, Practice systems, Presentation Anxiety, Public speaking, Q&A practice, user experience, Users' experiences, Virtual environments, Virtual Reality, VR training},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper introduces a novel VR-based Q&A practice system that harnesses the power of Large Language Models (LLMs). We support Q&A practice for upcoming public speaking by providing an immersive VR training environment populated with LLM-generated audiences, each capable of posing diverse and realistic questions based on different personas. We conducted a pilot user study involving 20 participants who engaged in VR-based Q&A practice sessions. The sessions featured a variety of questions regarding presentation material provided by the participants, all of which were generated by LLM-based personas. Through post-surveys and interviews, we evaluated the effectiveness of the proposed method. The participants valued the system for engagement and focus while also identifying several areas for improvement. Our study demonstrated the potential of integrating VR and LLMs to create a powerful, immersive tool for Q&A practice. © 2024 IEEE.
Tang, Y.; Situ, J.; Huang, Y.
Beyond User Experience: Technical and Contextual Metrics for Large Language Models in Extended Reality Proceedings Article
In: UbiComp Companion - Companion ACM Int. Jt. Conf. Pervasive Ubiquitous Comput., pp. 640–643, Association for Computing Machinery, Inc, 2024, ISBN: 979-840071058-2 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented Reality, Computer simulation languages, Evaluation Metrics, Extended reality, Language Model, Large language model, large language models, Mixed reality, Modeling performance, Natural language processing systems, Physical world, Spatial computing, spatial data, user experience, Users' experiences, Virtual environments, Virtual Reality
@inproceedings{tang_beyond_2024,
title = {Beyond User Experience: Technical and Contextual Metrics for Large Language Models in Extended Reality},
author = {Y. Tang and J. Situ and Y. Huang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206203437&doi=10.1145%2f3675094.3678995&partnerID=40&md5=3fb337872b483a163bfbea038f1baffe},
doi = {10.1145/3675094.3678995},
isbn = {979-840071058-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {UbiComp Companion - Companion ACM Int. Jt. Conf. Pervasive Ubiquitous Comput.},
pages = {640–643},
publisher = {Association for Computing Machinery, Inc},
abstract = {Spatial Computing involves interacting with the physical world through spatial data manipulation, closely linked with Extended Reality (XR), which includes Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Large Language Models (LLMs) significantly enhance XR applications by improving user interactions through natural language understanding and content generation. Typical evaluations of these applications focus on user experience (UX) metrics, such as task performance, user satisfaction, and psychological assessments, but often neglect the technical performance of the LLMs themselves. This paper identifies significant gaps in current evaluation practices for LLMs within XR environments, attributing them to the novelty of the field, the complexity of spatial contexts, and the multimodal nature of interactions in XR. To address these gaps, the paper proposes specific metrics tailored to evaluate LLM performance in XR contexts, including spatial contextual awareness, coherence, proactivity, multimodal integration, hallucination, and question-answering accuracy. These proposed metrics aim to complement existing UX evaluations, providing a comprehensive assessment framework that captures both the technical and user-centric aspects of LLM performance in XR applications. The conclusion underscores the necessity for a dual-focused approach that combines technical and UX metrics to ensure effective and user-friendly LLM-integrated XR systems. © 2024 Copyright held by the owner/author(s).},
keywords = {Augmented Reality, Computer simulation languages, Evaluation Metrics, Extended reality, Language Model, Large language model, large language models, Mixed reality, Modeling performance, Natural language processing systems, Physical world, Spatial computing, spatial data, user experience, Users' experiences, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Spatial Computing involves interacting with the physical world through spatial data manipulation, closely linked with Extended Reality (XR), which includes Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Large Language Models (LLMs) significantly enhance XR applications by improving user interactions through natural language understanding and content generation. Typical evaluations of these applications focus on user experience (UX) metrics, such as task performance, user satisfaction, and psychological assessments, but often neglect the technical performance of the LLMs themselves. This paper identifies significant gaps in current evaluation practices for LLMs within XR environments, attributing them to the novelty of the field, the complexity of spatial contexts, and the multimodal nature of interactions in XR. To address these gaps, the paper proposes specific metrics tailored to evaluate LLM performance in XR contexts, including spatial contextual awareness, coherence, proactivity, multimodal integration, hallucination, and question-answering accuracy. These proposed metrics aim to complement existing UX evaluations, providing a comprehensive assessment framework that captures both the technical and user-centric aspects of LLM performance in XR applications. The conclusion underscores the necessity for a dual-focused approach that combines technical and UX metrics to ensure effective and user-friendly LLM-integrated XR systems. © 2024 Copyright held by the owner/author(s).