AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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Here you can find the complete list of our publications.
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You can expand the Abstract, Links and BibTex record for each paper.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Alex, G.
Leveraging Large Language Models for Automated XR Instructional Content Generation Proceedings Article
In: Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331585341 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Authoring Tool, Case-studies, Engineering education, Extended reality, IEEE Standards, Language Model, Large language model, Learning systems, Ontology, Ontology's, Simple++
@inproceedings{alex_leveraging_2025,
title = {Leveraging Large Language Models for Automated XR Instructional Content Generation},
author = {G. Alex},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015398440&doi=10.1109%2FICE%2FITMC65658.2025.11106622&partnerID=40&md5=c125d3b7e58cfff4c24a9b15bb615912},
doi = {10.1109/ICE/ITMC65658.2025.11106622},
isbn = {9798331585341 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This paper presents a study in which authors examine the potential of leveraging large language models to generate instructional content for eXtended Reality environments. Considering the IEEE ARLEM standard as a framework for structuring data, it could be integrated and interpreted by existing authoring tools. In terms of methods, authors have adopted an exploratory approach in testing various strategies. A case study focusing on the use of an eXtended Reality authoring tool for teaching operating procedures is presented. Finally, this exploratory work shows that while simple prompts can produce scenarios with satisfactory quality, imposing a structured schema through more complex prompts leads to less reliable outcomes. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Artificial intelligence, Authoring Tool, Case-studies, Engineering education, Extended reality, IEEE Standards, Language Model, Large language model, Learning systems, Ontology, Ontology's, Simple++},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a study in which authors examine the potential of leveraging large language models to generate instructional content for eXtended Reality environments. Considering the IEEE ARLEM standard as a framework for structuring data, it could be integrated and interpreted by existing authoring tools. In terms of methods, authors have adopted an exploratory approach in testing various strategies. A case study focusing on the use of an eXtended Reality authoring tool for teaching operating procedures is presented. Finally, this exploratory work shows that while simple prompts can produce scenarios with satisfactory quality, imposing a structured schema through more complex prompts leads to less reliable outcomes. © 2025 Elsevier B.V., All rights reserved.
Saddik, A. El; Ahmad, J.; Khan, M.; Abouzahir, S.; Gueaieb, W.
Unleashing Creativity in the Metaverse: Generative AI and Multimodal Content Journal Article
In: ACM Transactions on Multimedia Computing, Communications and Applications, vol. 21, no. 7, pp. 1–43, 2025, ISSN: 15516857 (ISSN); 15516865 (ISSN), (Publisher: Association for Computing Machinery).
Abstract | Links | BibTeX | Tags: Adversarial networks, Artificial intelligence, Content generation, Context information, Creatives, Diffusion Model, diffusion models, Generative adversarial networks, Generative AI, Human engineering, Information instructions, Interactive computer graphics, Interactive computer systems, Interactive devices, Interoperability, Metaverse, Metaverses, Multi-modal, multimodal, Simple++, Three dimensional computer graphics, user experience, User interfaces, Virtual Reality
@article{el_saddik_unleashing_2025,
title = {Unleashing Creativity in the Metaverse: Generative AI and Multimodal Content},
author = {A. El Saddik and J. Ahmad and M. Khan and S. Abouzahir and W. Gueaieb},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011860002&doi=10.1145%2F3713075&partnerID=40&md5=20064843ced240c42e9353d747672cb3},
doi = {10.1145/3713075},
issn = {15516857 (ISSN); 15516865 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {ACM Transactions on Multimedia Computing, Communications and Applications},
volume = {21},
number = {7},
pages = {1–43},
abstract = {The metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple prompts. These prompts allow the metaverse to interact with GenAI, where context information, instructions, input data, or even output indications constituting the prompt can come from within the metaverse. However, their integration poses challenges regarding interoperability, lack of standards, scalability, and maintaining a high-quality user experience. This article explores how GenAI can productively assist in enhancing creativity within the contexts of the metaverse and unlock new opportunities. We provide a technical, in-depth overview of the different generative models for image, video, audio, and 3D content within the metaverse environments. We also explore the bottlenecks, opportunities, and innovative applications of GenAI from the perspectives of end users, developers, service providers, and AI researchers. This survey commences by highlighting the potential of GenAI for enhancing the metaverse experience through dynamic content generation to populate massive virtual worlds. Subsequently, we shed light on the ongoing research practices and trends in multimodal content generation, enhancing realism and creativity and alleviating bottlenecks related to standardization, computational cost, privacy, and safety. Last, we share insights into promising research directions toward the integration of GenAI with the metaverse for creative enhancement, improved immersion, and innovative interactive applications. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Association for Computing Machinery},
keywords = {Adversarial networks, Artificial intelligence, Content generation, Context information, Creatives, Diffusion Model, diffusion models, Generative adversarial networks, Generative AI, Human engineering, Information instructions, Interactive computer graphics, Interactive computer systems, Interactive devices, Interoperability, Metaverse, Metaverses, Multi-modal, multimodal, Simple++, Three dimensional computer graphics, user experience, User interfaces, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
The metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple prompts. These prompts allow the metaverse to interact with GenAI, where context information, instructions, input data, or even output indications constituting the prompt can come from within the metaverse. However, their integration poses challenges regarding interoperability, lack of standards, scalability, and maintaining a high-quality user experience. This article explores how GenAI can productively assist in enhancing creativity within the contexts of the metaverse and unlock new opportunities. We provide a technical, in-depth overview of the different generative models for image, video, audio, and 3D content within the metaverse environments. We also explore the bottlenecks, opportunities, and innovative applications of GenAI from the perspectives of end users, developers, service providers, and AI researchers. This survey commences by highlighting the potential of GenAI for enhancing the metaverse experience through dynamic content generation to populate massive virtual worlds. Subsequently, we shed light on the ongoing research practices and trends in multimodal content generation, enhancing realism and creativity and alleviating bottlenecks related to standardization, computational cost, privacy, and safety. Last, we share insights into promising research directions toward the integration of GenAI with the metaverse for creative enhancement, improved immersion, and innovative interactive applications. © 2025 Elsevier B.V., All rights reserved.
2024
Shrestha, A.; Imamoto, K.
Generative AI based industrial metaverse creation methodology Proceedings Article
In: Proc. - Artif. Intell. Bus., AIxB, pp. 53–57, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 9798350391039 (ISBN).
Abstract | Links | BibTeX | Tags: Generative adversarial networks, Generative AI, Industrial metaverse, Industrial railroads, Investments, Maintenance and operation, Metaverses, Natural languages, Railroad transportation, Railway, Railway maintenance, Railway operations, Simple++, simulation
@inproceedings{shrestha_generative_2024,
title = {Generative AI based industrial metaverse creation methodology},
author = {A. Shrestha and K. Imamoto},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215066217&doi=10.1109%2FAIxB62249.2024.00017&partnerID=40&md5=5ca8685cccb97c28d52a12d511f05aaf},
doi = {10.1109/AIxB62249.2024.00017},
isbn = {9798350391039 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - Artif. Intell. Bus., AIxB},
pages = {53–57},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The metaverse has been proposed as a suitable apparatus for the dissemination of information in a railway maintenance and operation context. However, the generation of such a metaverse environment requires significant investment with the creation of simple prototypes taking an extended duration. Although there are generative artificial intelligencebased methods to create small scenes, there is an absence of a method to do so for industrial applications. We devised a platform to create railway environments with the assistance of the language models for code creation and semantic inference without the need for reprogramming or editing of the project source meaning environments could be generated by the end users. With a natural language input and a coding paradigm output the code generation module is shown together with the example environments from real-life railway lines in Tokyo, Japan as preliminary results. By creating such environments leveraging the rapid generation with the help of generative artificial intelligence, we show generative artificial intelligence can be used to automate the task of the programmer to create new environments on demand from the user in natural language. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Generative adversarial networks, Generative AI, Industrial metaverse, Industrial railroads, Investments, Maintenance and operation, Metaverses, Natural languages, Railroad transportation, Railway, Railway maintenance, Railway operations, Simple++, simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
The metaverse has been proposed as a suitable apparatus for the dissemination of information in a railway maintenance and operation context. However, the generation of such a metaverse environment requires significant investment with the creation of simple prototypes taking an extended duration. Although there are generative artificial intelligencebased methods to create small scenes, there is an absence of a method to do so for industrial applications. We devised a platform to create railway environments with the assistance of the language models for code creation and semantic inference without the need for reprogramming or editing of the project source meaning environments could be generated by the end users. With a natural language input and a coding paradigm output the code generation module is shown together with the example environments from real-life railway lines in Tokyo, Japan as preliminary results. By creating such environments leveraging the rapid generation with the help of generative artificial intelligence, we show generative artificial intelligence can be used to automate the task of the programmer to create new environments on demand from the user in natural language. © 2025 Elsevier B.V., All rights reserved.
2023
Horváth, I.; Csapó, A. B.
Structured Template Language and Generative AI Driven Content Management for Personalized Workspace Reconfiguration Proceedings Article
In: IEEE Int. Conf. Cogn. Asp. Virtual Real., CVR, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 9798350338638 (ISBN).
Abstract | Links | BibTeX | Tags: 3D spaces, 3D virtual reality, Cognitive infocommunications, Content management, Content management solutions, Geometric layout, Knowledge engineering, Semantic content, Semantic content management, Semantics, Simple++, Virtual Reality, Work-flows
@inproceedings{horvath_structured_2023,
title = {Structured Template Language and Generative AI Driven Content Management for Personalized Workspace Reconfiguration},
author = {I. Horváth and A. B. Csapó},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184849596&doi=10.1109%2FCVR58941.2023.10395520&partnerID=40&md5=68156a991f9af4a359e630d622e58176},
doi = {10.1109/CVR58941.2023.10395520},
isbn = {9798350338638 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {IEEE Int. Conf. Cogn. Asp. Virtual Real., CVR},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This work presents a systematic approach towards personalized workspace management and reconfiguration in 3D Virtual Reality (VR) spaces, focusing on a structured template language for defining and manipulating content layout schemas, as well as a generative AI supported content management solution. Recognizing the varying requirements of different tasks and workflows, on the one hand we propose a hierarchical template language that enables, through simple steps, the adaptation of number and variety of documents within geometric layout schemas in digital 3D spaces. In the second half of the paper, we present a generative AI driven framework for integrating associative-semantic content management into such workspaces, thereby enhancing the relevance and contextuality of workspace configurations. The proposed approach aids in identifying content that is semantically linked to a given spatial, temporal and topical environment, enabling workspace designers and users to create more efficient and personalized workspace layouts. © 2024 Elsevier B.V., All rights reserved.},
keywords = {3D spaces, 3D virtual reality, Cognitive infocommunications, Content management, Content management solutions, Geometric layout, Knowledge engineering, Semantic content, Semantic content management, Semantics, Simple++, Virtual Reality, Work-flows},
pubstate = {published},
tppubtype = {inproceedings}
}
This work presents a systematic approach towards personalized workspace management and reconfiguration in 3D Virtual Reality (VR) spaces, focusing on a structured template language for defining and manipulating content layout schemas, as well as a generative AI supported content management solution. Recognizing the varying requirements of different tasks and workflows, on the one hand we propose a hierarchical template language that enables, through simple steps, the adaptation of number and variety of documents within geometric layout schemas in digital 3D spaces. In the second half of the paper, we present a generative AI driven framework for integrating associative-semantic content management into such workspaces, thereby enhancing the relevance and contextuality of workspace configurations. The proposed approach aids in identifying content that is semantically linked to a given spatial, temporal and topical environment, enabling workspace designers and users to create more efficient and personalized workspace layouts. © 2024 Elsevier B.V., All rights reserved.