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
Miller, C. H.
Digital Storytelling: A Creator’s Guide to Interactive Entertainment: Volume I, Fifth Edition Book
CRC Press, 2025, ISBN: 978-104034442-2 (ISBN); 978-103285888-3 (ISBN).
Abstract | Links | BibTeX | Tags: Case-studies, Chatbots, Creatives, Digital storytelling, Entertainment, Immersive environment, Interactive documentary, Interactive entertainment, Social media, Use of video, Video-games, Virtual Reality
@book{miller_digital_2025,
title = {Digital Storytelling: A Creator’s Guide to Interactive Entertainment: Volume I, Fifth Edition},
author = {C. H. Miller},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004122515&doi=10.1201%2f9781003520092&partnerID=40&md5=894bfbb310cbd095a54409f9ac5174da},
doi = {10.1201/9781003520092},
isbn = {978-104034442-2 (ISBN); 978-103285888-3 (ISBN)},
year = {2025},
date = {2025-01-01},
volume = {1},
publisher = {CRC Press},
series = {Digital Storytelling: a Creator's Guide to Interactive Entertainment: Volume I, Fifth Edition},
abstract = {Digital Storytelling: A Creator’s Guide to Interactive Entertainment, Volume I, fifth edition delves into the fascinating and groundbreaking stories enabled by interactive digital media, examining both fictional and non-fiction narratives. This fifth edition explores monumental developments, particularly the emergence of generative AI, and highlights exciting projects utilizing this technology. Additionally, it covers social media; interactive documentaries; immersive environments; and innovative uses of video games, chatbots, and virtual reality. Carolyn Handler Miller provides insights into storytelling essentials like character development, plot, structure, dialogue, and emotion, while examining how digital media and interactivity influence these elements. This book also dives into advanced topics, such as narratives using AR, VR, and XR, alongside new forms of immersive media, including large screens, escape rooms, and theme park experiences. With numerous case studies, this edition illustrates the creative possibilities of digital storytelling and its applications beyond entertainment, such as education, training, information, and promotion. Interviews with industry leaders further enhance the understanding of this evolving universe, making it a valuable resource for both professionals and enthusiasts. Key Features: • This book includes up-to-the-minute developments in digital storytelling. • It offers case studies of noteworthy examples of digital storytelling. • It includes a glossary clearly defining new or difficult terms. • Each chapter opens with several thought-provoking questions about the chapter’s topic. • Each chapter concludes with several creative and engaging exercises to promote the reader’s understanding of the chapter’s topic. © 2025 Carolyn Handler Miller.},
keywords = {Case-studies, Chatbots, Creatives, Digital storytelling, Entertainment, Immersive environment, Interactive documentary, Interactive entertainment, Social media, Use of video, Video-games, Virtual Reality},
pubstate = {published},
tppubtype = {book}
}
Digital Storytelling: A Creator’s Guide to Interactive Entertainment, Volume I, fifth edition delves into the fascinating and groundbreaking stories enabled by interactive digital media, examining both fictional and non-fiction narratives. This fifth edition explores monumental developments, particularly the emergence of generative AI, and highlights exciting projects utilizing this technology. Additionally, it covers social media; interactive documentaries; immersive environments; and innovative uses of video games, chatbots, and virtual reality. Carolyn Handler Miller provides insights into storytelling essentials like character development, plot, structure, dialogue, and emotion, while examining how digital media and interactivity influence these elements. This book also dives into advanced topics, such as narratives using AR, VR, and XR, alongside new forms of immersive media, including large screens, escape rooms, and theme park experiences. With numerous case studies, this edition illustrates the creative possibilities of digital storytelling and its applications beyond entertainment, such as education, training, information, and promotion. Interviews with industry leaders further enhance the understanding of this evolving universe, making it a valuable resource for both professionals and enthusiasts. Key Features: • This book includes up-to-the-minute developments in digital storytelling. • It offers case studies of noteworthy examples of digital storytelling. • It includes a glossary clearly defining new or difficult terms. • Each chapter opens with several thought-provoking questions about the chapter’s topic. • Each chapter concludes with several creative and engaging exercises to promote the reader’s understanding of the chapter’s topic. © 2025 Carolyn Handler Miller.
Graziano, M.; Cante, L. Colucci; Martino, B. Di
Deploying Large Language Model on Cloud-Edge Architectures: A Case Study for Conversational Historical Characters Book Section
In: Lecture Notes on Data Engineering and Communications Technologies, vol. 250, pp. 196–205, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 23674512 (ISSN).
Abstract | Links | BibTeX | Tags: Agent based, Augmented Reality, Case-studies, Chatbots, Cloud computing architecture, Conversational Agents, EDGE architectures, Historical characters, Language Model, Modeling languages, Real time performance, WEB application, Web applications, Work analysis
@incollection{graziano_deploying_2025,
title = {Deploying Large Language Model on Cloud-Edge Architectures: A Case Study for Conversational Historical Characters},
author = {M. Graziano and L. Colucci Cante and B. Di Martino},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002995405&doi=10.1007%2f978-3-031-87778-0_19&partnerID=40&md5=c54e9ce66901050a05de68602e4a8266},
doi = {10.1007/978-3-031-87778-0_19},
isbn = {23674512 (ISSN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lecture Notes on Data Engineering and Communications Technologies},
volume = {250},
pages = {196–205},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This work analyzes the deployment of conversational agents based on large language models (LLMs) in cloud-edge architectures, placing emphasis on scalability, efficiency and real-time performance. Through a case study, we present a web application that allows users to interact with an augmented reality avatar that impersonates a historical character. The agent, powered by an LLM delivers immersive and contextually coherent dialogues. We discuss the solutions adopted to manage latency and distribute the computational load between the cloud, which takes care of language processing, and the edge nodes, ensuring a smooth user experience. The results obtained demonstrate how accurate design can optimize the use of LLMs in distributed environments, offering advanced and high-performance interactions even in applications with high reactivity and customization requirements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {Agent based, Augmented Reality, Case-studies, Chatbots, Cloud computing architecture, Conversational Agents, EDGE architectures, Historical characters, Language Model, Modeling languages, Real time performance, WEB application, Web applications, Work analysis},
pubstate = {published},
tppubtype = {incollection}
}
This work analyzes the deployment of conversational agents based on large language models (LLMs) in cloud-edge architectures, placing emphasis on scalability, efficiency and real-time performance. Through a case study, we present a web application that allows users to interact with an augmented reality avatar that impersonates a historical character. The agent, powered by an LLM delivers immersive and contextually coherent dialogues. We discuss the solutions adopted to manage latency and distribute the computational load between the cloud, which takes care of language processing, and the edge nodes, ensuring a smooth user experience. The results obtained demonstrate how accurate design can optimize the use of LLMs in distributed environments, offering advanced and high-performance interactions even in applications with high reactivity and customization requirements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
2024
Qin, X.; Weaver, G.
Utilizing Generative AI for VR Exploration Testing: A Case Study Proceedings Article
In: Proc. - ACM/IEEE Int. Conf. Autom. Softw. Eng. Workshops, ASEW, pp. 228–232, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-840071249-4 (ISBN).
Abstract | Links | BibTeX | Tags: Ability testing, Accuracy rate, Case Study, Case-studies, Entity selections, Field of views, Generative adversarial networks, GUI Exploration Testing, GUI testing, Localisation, Long term memory, Mixed data, Object identification, Object recognition, Virtual environments, Virtual Reality
@inproceedings{qin_utilizing_2024,
title = {Utilizing Generative AI for VR Exploration Testing: A Case Study},
author = {X. Qin and G. Weaver},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213332710&doi=10.1145%2f3691621.3694955&partnerID=40&md5=8f3dc03520214cd2e270ed41a0fc0e19},
doi = {10.1145/3691621.3694955},
isbn = {979-840071249-4 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - ACM/IEEE Int. Conf. Autom. Softw. Eng. Workshops, ASEW},
pages = {228–232},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {As the virtual reality (VR) industry expands, the need for automated GUI testing for applications is growing rapidly. With its long-term memory and ability to process mixed data, including images and text, Generative AI (GenAI) shows the potential to understand complex user interfaces. In this paper, we conduct a case study to investigate the potential of using GenAI for field of view (FOV) analysis in VR exploration testing. Specifically, we examine how the model can assist in test entity selection and test action suggestions. Our experiments demonstrate that while GPT-4o achieves a 63% accuracy rate in object identification within an arbitrary FOV, it struggles with object organization and localization. We also identify critical contexts that can improve the accuracy of suggested actions across multiple FOVs. Finally, we discuss the limitations found during the experiment and offer insights into future research directions. © 2024 ACM.},
keywords = {Ability testing, Accuracy rate, Case Study, Case-studies, Entity selections, Field of views, Generative adversarial networks, GUI Exploration Testing, GUI testing, Localisation, Long term memory, Mixed data, Object identification, Object recognition, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
As the virtual reality (VR) industry expands, the need for automated GUI testing for applications is growing rapidly. With its long-term memory and ability to process mixed data, including images and text, Generative AI (GenAI) shows the potential to understand complex user interfaces. In this paper, we conduct a case study to investigate the potential of using GenAI for field of view (FOV) analysis in VR exploration testing. Specifically, we examine how the model can assist in test entity selection and test action suggestions. Our experiments demonstrate that while GPT-4o achieves a 63% accuracy rate in object identification within an arbitrary FOV, it struggles with object organization and localization. We also identify critical contexts that can improve the accuracy of suggested actions across multiple FOVs. Finally, we discuss the limitations found during the experiment and offer insights into future research directions. © 2024 ACM.
Amato, N.; Carolis, B. De; Gioia, F.; Venezia, M. N.; Palestra, G.; Loglisci, C.
Can an AI-driven VTuber engage People? The KawAIi Case Study Proceedings Article
In: A., Soto; E., Zangerle (Ed.): CEUR Workshop Proc., CEUR-WS, 2024, ISBN: 16130073 (ISSN).
Abstract | Links | BibTeX | Tags: 3D Avatars, Case-studies, Conversational Agents, Facial Expressions, Language Model, Live streaming, LLM, LLMs, Real- time, Three dimensional computer graphics, Virtual agent, Virtual Reality, YouTube
@inproceedings{amato_can_2024,
title = {Can an AI-driven VTuber engage People? The KawAIi Case Study},
author = {N. Amato and B. De Carolis and F. Gioia and M. N. Venezia and G. Palestra and C. Loglisci},
editor = {Soto A. and Zangerle E.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190754935&partnerID=40&md5=bd76d56b13e328027aa1b458849cf73f},
isbn = {16130073 (ISSN)},
year = {2024},
date = {2024-01-01},
booktitle = {CEUR Workshop Proc.},
volume = {3660},
publisher = {CEUR-WS},
abstract = {Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership. This paper presents the development of a conversational agent, named KawAIi, embodied in a 2D character that, while accurately and promptly responding to user requests, provides an entertaining experience in streaming chat platforms such as YouTube while providing adequate real-time support. The agent relies on the Vicuna 7B GPTQ 4-bit Large Language Model (LLM). In addition, KawAIi uses a BERT-based model for analyzing the sentence generated by the model in terms of conveyed emotion and shows self-emotion awareness through facial expressions. Tested with users, the system has demonstrated a good ability to handle the interaction with the user while maintaining a pleasant user experience. In particular, KawAIi has been evaluated positively in terms of engagement and competence on various topics. The results show the potential of this technology to enrich interactivity in streaming platforms and offer a promising model for future online assistance contexts. © 2024 Copyright for this paper by its authors.},
keywords = {3D Avatars, Case-studies, Conversational Agents, Facial Expressions, Language Model, Live streaming, LLM, LLMs, Real- time, Three dimensional computer graphics, Virtual agent, Virtual Reality, YouTube},
pubstate = {published},
tppubtype = {inproceedings}
}
Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership. This paper presents the development of a conversational agent, named KawAIi, embodied in a 2D character that, while accurately and promptly responding to user requests, provides an entertaining experience in streaming chat platforms such as YouTube while providing adequate real-time support. The agent relies on the Vicuna 7B GPTQ 4-bit Large Language Model (LLM). In addition, KawAIi uses a BERT-based model for analyzing the sentence generated by the model in terms of conveyed emotion and shows self-emotion awareness through facial expressions. Tested with users, the system has demonstrated a good ability to handle the interaction with the user while maintaining a pleasant user experience. In particular, KawAIi has been evaluated positively in terms of engagement and competence on various topics. The results show the potential of this technology to enrich interactivity in streaming platforms and offer a promising model for future online assistance contexts. © 2024 Copyright for this paper by its authors.
Rausa, M.; Gaglio, S.; Augello, A.; Caggianese, G.; Franchini, S.; Gallo, L.; Sabatucci, L.
Enriching Metaverse with Memories Through Generative AI: A Case Study Proceedings Article
In: IEEE Int. Conf. Metrol. Ext. Real., Artif. Intell. Neural Eng., MetroXRAINE - Proc., pp. 371–376, Institute of Electrical and Electronics Engineers Inc., St Albans, United Kingdom, 2024, ISBN: 979-835037800-9 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3D reconstruction, 3d-modeling, Case-studies, Generative adversarial networks, Generative AI, Input modes, Metamemory, Metaverses, Synthetic Data Generation, Synthetic data generations, Textual description, Virtual environments, Virtual Reality
@inproceedings{rausa_enriching_2024,
title = {Enriching Metaverse with Memories Through Generative AI: A Case Study},
author = {M. Rausa and S. Gaglio and A. Augello and G. Caggianese and S. Franchini and L. Gallo and L. Sabatucci},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216124702&doi=10.1109%2fMetroXRAINE62247.2024.10796338&partnerID=40&md5=580d0727ab8740a6ada62eeef5ac283f},
doi = {10.1109/MetroXRAINE62247.2024.10796338},
isbn = {979-835037800-9 (ISBN)},
year = {2024},
date = {2024-01-01},
urldate = {2025-01-07},
booktitle = {IEEE Int. Conf. Metrol. Ext. Real., Artif. Intell. Neural Eng., MetroXRAINE - Proc.},
pages = {371–376},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
address = {St Albans, United Kingdom},
abstract = {The paper introduces MetaMemory, an approach to generate 3D models from either textual descriptions or photographs of objects, offering dual input modes for enhanced representation. MetaMemory's architecture is discussed presenting the tools employed in extracting the object from the image, generating the 3D mesh from texts or images, and visualizing the object reconstruction in an immersive scenario. Afterwards, a case study in which we experienced reconstructing memories of ancient crafts is examined together with the achieved results, by highlighting current limitations and potential applications. © 2024 IEEE.},
keywords = {3D modeling, 3D models, 3D reconstruction, 3d-modeling, Case-studies, Generative adversarial networks, Generative AI, Input modes, Metamemory, Metaverses, Synthetic Data Generation, Synthetic data generations, Textual description, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper introduces MetaMemory, an approach to generate 3D models from either textual descriptions or photographs of objects, offering dual input modes for enhanced representation. MetaMemory's architecture is discussed presenting the tools employed in extracting the object from the image, generating the 3D mesh from texts or images, and visualizing the object reconstruction in an immersive scenario. Afterwards, a case study in which we experienced reconstructing memories of ancient crafts is examined together with the achieved results, by highlighting current limitations and potential applications. © 2024 IEEE.