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 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
Lau, K. H. C.; Bozkir, E.; Gao, H.; Kasneci, E.
Evaluating Usability and Engagement of Large Language Models in Virtual Reality for Traditional Scottish Curling Proceedings Article
In: A., Del Bue; C., Canton; J., Pont-Tuset; T., Tommasi (Ed.): Lect. Notes Comput. Sci., pp. 177–195, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-303191571-0 (ISBN).
Abstract | Links | BibTeX | Tags: Chatbots, Cultural heritages, Digital Cultural Heritage, Digital cultural heritages, Educational robots, Engineering education, Heritage education, Historic Preservation, Language Model, Large language model, large language models, Learning outcome, Model-based OPC, Usability engineering, User Engagement, Virtual Reality, Virtual-reality environment, Virtualization
@inproceedings{lau_evaluating_2025,
title = {Evaluating Usability and Engagement of Large Language Models in Virtual Reality for Traditional Scottish Curling},
author = {K. H. C. Lau and E. Bozkir and H. Gao and E. Kasneci},
editor = {Del Bue A. and Canton C. and Pont-Tuset J. and Tommasi T.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105006905979&doi=10.1007%2f978-3-031-91572-7_11&partnerID=40&md5=8a81fb09ff54e57b9429660a8898149a},
doi = {10.1007/978-3-031-91572-7_11},
isbn = {03029743 (ISSN); 978-303191571-0 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15628 LNCS},
pages = {177–195},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This paper explores the innovative application of Large Language Models (LLMs) in Virtual Reality (VR) environments to promote heritage education, focusing on traditional Scottish curling presented in the game “Scottish Bonspiel VR”. Our study compares the effectiveness of LLM-based chatbots with pre-defined scripted chatbots, evaluating key criteria such as usability, user engagement, and learning outcomes. The results show that LLM-based chatbots significantly improve interactivity and engagement, creating a more dynamic and immersive learning environment. This integration helps document and preserve cultural heritage and enhances dissemination processes, which are crucial for safeguarding intangible cultural heritage (ICH) amid environmental changes. Furthermore, the study highlights the potential of novel technologies in education to provide immersive experiences that foster a deeper appreciation of cultural heritage. These findings support the wider application of LLMs and VR in cultural education to address global challenges and promote sustainable practices to preserve and enhance cultural heritage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {Chatbots, Cultural heritages, Digital Cultural Heritage, Digital cultural heritages, Educational robots, Engineering education, Heritage education, Historic Preservation, Language Model, Large language model, large language models, Learning outcome, Model-based OPC, Usability engineering, User Engagement, Virtual Reality, Virtual-reality environment, Virtualization},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper explores the innovative application of Large Language Models (LLMs) in Virtual Reality (VR) environments to promote heritage education, focusing on traditional Scottish curling presented in the game “Scottish Bonspiel VR”. Our study compares the effectiveness of LLM-based chatbots with pre-defined scripted chatbots, evaluating key criteria such as usability, user engagement, and learning outcomes. The results show that LLM-based chatbots significantly improve interactivity and engagement, creating a more dynamic and immersive learning environment. This integration helps document and preserve cultural heritage and enhances dissemination processes, which are crucial for safeguarding intangible cultural heritage (ICH) amid environmental changes. Furthermore, the study highlights the potential of novel technologies in education to provide immersive experiences that foster a deeper appreciation of cultural heritage. These findings support the wider application of LLMs and VR in cultural education to address global challenges and promote sustainable practices to preserve and enhance cultural heritage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Guo, H.; Liu, Z.; Tang, C.; Zhang, X.
An Interactive Framework for Personalized Navigation Based on Metacosmic Cultural Tourism and Large Model Fine-Tuning Journal Article
In: IEEE Access, vol. 13, pp. 81450–81461, 2025, ISSN: 21693536 (ISSN).
Abstract | Links | BibTeX | Tags: Cultural informations, Digital Cultural Heritage, Digital cultural heritages, Digital guide, Fine tuning, fine-tuning, Historical monuments, Language Model, Large language model, Leisure, Metacosmic cultural tourism, Multimodal Interaction, Tourism, Virtual tour
@article{guo_interactive_2025,
title = {An Interactive Framework for Personalized Navigation Based on Metacosmic Cultural Tourism and Large Model Fine-Tuning},
author = {H. Guo and Z. Liu and C. Tang and X. Zhang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004059236&doi=10.1109%2fACCESS.2025.3565359&partnerID=40&md5=45d328831c5795fa31e7e033299912b5},
doi = {10.1109/ACCESS.2025.3565359},
issn = {21693536 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Access},
volume = {13},
pages = {81450–81461},
abstract = {With the wide application of large language models (LLMs) and the rapid growth of metaverse tourism demand, the digital tour and personalized interaction of historical sites have become the key to improving users’ digital travel experience. Creating an environment where users can access rich cultural information and enjoy personalized, immersive experiences is a crucial issue in the field of digital cultural travel. To this end, we propose a tourism information multimodal generation personalized question-answering interactive framework TIGMI (Tourism Information Generation and Multimodal Interaction) based on LLM fine-tuning, which aims to provide a richer and more in-depth experience for virtual tours of historical monuments. Taking Qutan Temple as an example, the framework combines LLM, retrieval augmented generation (RAG), and auto-prompting engineering techniques to retrieve accurate information related to the historical monument from external knowledge bases and seamlessly integrates it into the generated content. This integration mechanism ensures the accuracy and relevance of the generated answers. Through TIGMI’s LLM-driven command interaction mechanism in the 3D digital scene of Qutan Temple, users are able to interact with the building and scene environment in a personalized and real-time manner, successfully integrating historical and cultural information with modern digital technology. This integration significantly enhances the naturalness of interaction and personalizes the user experience, thereby improving user immersion and information acquisition efficiency. Evaluation results show that TIGMI excels in question-answering and multimodal interactions, significantly enhancing the depth and breadth of services provided by the personalized virtual tour. We conclude by addressing the limitations of TIGMI and briefly discuss how future research will focus on further improving the accuracy and user satisfaction of the generated content to adapt to the dynamically changing tourism environment. © 2013 IEEE.},
keywords = {Cultural informations, Digital Cultural Heritage, Digital cultural heritages, Digital guide, Fine tuning, fine-tuning, Historical monuments, Language Model, Large language model, Leisure, Metacosmic cultural tourism, Multimodal Interaction, Tourism, Virtual tour},
pubstate = {published},
tppubtype = {article}
}
With the wide application of large language models (LLMs) and the rapid growth of metaverse tourism demand, the digital tour and personalized interaction of historical sites have become the key to improving users’ digital travel experience. Creating an environment where users can access rich cultural information and enjoy personalized, immersive experiences is a crucial issue in the field of digital cultural travel. To this end, we propose a tourism information multimodal generation personalized question-answering interactive framework TIGMI (Tourism Information Generation and Multimodal Interaction) based on LLM fine-tuning, which aims to provide a richer and more in-depth experience for virtual tours of historical monuments. Taking Qutan Temple as an example, the framework combines LLM, retrieval augmented generation (RAG), and auto-prompting engineering techniques to retrieve accurate information related to the historical monument from external knowledge bases and seamlessly integrates it into the generated content. This integration mechanism ensures the accuracy and relevance of the generated answers. Through TIGMI’s LLM-driven command interaction mechanism in the 3D digital scene of Qutan Temple, users are able to interact with the building and scene environment in a personalized and real-time manner, successfully integrating historical and cultural information with modern digital technology. This integration significantly enhances the naturalness of interaction and personalizes the user experience, thereby improving user immersion and information acquisition efficiency. Evaluation results show that TIGMI excels in question-answering and multimodal interactions, significantly enhancing the depth and breadth of services provided by the personalized virtual tour. We conclude by addressing the limitations of TIGMI and briefly discuss how future research will focus on further improving the accuracy and user satisfaction of the generated content to adapt to the dynamically changing tourism environment. © 2013 IEEE.