AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2025

Li, Z.; Zhang, H.; Peng, C.; Peiris, R.

Exploring Large Language Model-Driven Agents for Environment-Aware Spatial Interactions and Conversations in Virtual Reality Role-Play Scenarios Proceedings Article

In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces, VR, pp. 1–11, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833153645-9 (ISBN).

Abstract | Links | BibTeX | Tags: Chatbots, Computer simulation languages, Context- awareness, context-awareness, Digital elevation model, Generative AI, Human-AI Interaction, Language Model, Large language model, large language models, Model agents, Role-play simulation, role-play simulations, Role-plays, Spatial interaction, Virtual environments, Virtual Reality, Virtual-reality environment

@inproceedings{li_exploring_2025,

title = {Exploring Large Language Model-Driven Agents for Environment-Aware Spatial Interactions and Conversations in Virtual Reality Role-Play Scenarios},

author = {Z. Li and H. Zhang and C. Peng and R. Peiris},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002706893&doi=10.1109%2fVR59515.2025.00025&partnerID=40&md5=60f22109e054c9035a0c2210bb797039},

doi = {10.1109/VR59515.2025.00025},

isbn = {979-833153645-9 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces, VR},

pages = {1–11},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Recent research has begun adopting Large Language Model (LLM) agents to enhance Virtual Reality (VR) interactions, creating immersive chatbot experiences. However, while current studies focus on generating dialogue from user speech inputs, their abilities to generate richer experiences based on the perception of LLM agents' VR environments and interaction cues remain unexplored. Hence, in this work, we propose an approach that enables LLM agents to perceive virtual environments and generate environment-aware interactions and conversations for an embodied human-AI interaction experience in VR environments. Here, we define a schema for describing VR environments and their interactions through text prompts. We evaluate the performance of our method through five role-play scenarios created using our approach in a study with 14 participants. The findings discuss the opportunities and challenges of our proposed approach for developing environment-aware LLM agents that facilitate spatial interactions and conversations within VR role-play scenarios. © 2025 IEEE.},

keywords = {Chatbots, Computer simulation languages, Context- awareness, context-awareness, Digital elevation model, Generative AI, Human-AI Interaction, Language Model, Large language model, large language models, Model agents, Role-play simulation, role-play simulations, Role-plays, Spatial interaction, Virtual environments, Virtual Reality, Virtual-reality environment},

pubstate = {published},

tppubtype = {inproceedings}

}

2024

Hong, J.; Lee, Y.; Kim, D. H.; Choi, D.; Yoon, Y. -J.; Lee, G. -C.; Lee, Z.; Kim, J.

A Context-Aware Onboarding Agent for Metaverse Powered by Large Language Models Proceedings Article

In: A., Vallgarda; L., Jonsson; J., Fritsch; S.F., Alaoui; C.A., Le Dantec (Ed.): Proc. ACM Des. Interact. Syst. Conf., pp. 1857–1874, Association for Computing Machinery, Inc, 2024, ISBN: 979-840070583-0 (ISBN).

Abstract | Links | BibTeX | Tags: 'current, Computational Linguistics, Context- awareness, Context-Aware, context-awareness, conversational agent, Conversational Agents, Divergents, Language Model, Large-language model, large-language models, Metaverse, Metaverses, Model-based OPC, Onboarding, User interfaces, Virtual Reality

@inproceedings{hong_context-aware_2024,

title = {A Context-Aware Onboarding Agent for Metaverse Powered by Large Language Models},

author = {J. Hong and Y. Lee and D. H. Kim and D. Choi and Y. -J. Yoon and G. -C. Lee and Z. Lee and J. Kim},

editor = {Vallgarda A. and Jonsson L. and Fritsch J. and Alaoui S.F. and Le Dantec C.A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200340104&doi=10.1145%2f3643834.3661579&partnerID=40&md5=5fe96b5155ca45c6d7a0d239b68f2b30},

doi = {10.1145/3643834.3661579},

isbn = {979-840070583-0 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. ACM Des. Interact. Syst. Conf.},

pages = {1857–1874},

publisher = {Association for Computing Machinery, Inc},

abstract = {One common asset of metaverse is that users can freely explore places and actions without linear procedures. Thus, it is hard yet important to understand the divergent challenges each user faces when onboarding metaverse. Our formative study (N = 16) shows that frst-time users ask questions about metaverse that concern 1) a short-term spatiotemporal context, regarding the user’s current location, recent conversation, and actions, and 2) a long-term exploration context regarding the user’s experience history. Based on the fndings, we present PICAN, a Large Language Model-based pipeline that generates context-aware answers to users when onboarding metaverse. An ablation study (N = 20) reveals that PICAN’s usage of context made responses more useful and immersive than those generated without contexts. Furthermore, a user study (N = 21) shows that the use of long-term exploration context promotes users’ learning about the locations and activities within the virtual environment. © 2024 Copyright held by the owner/author(s).},

keywords = {'current, Computational Linguistics, Context- awareness, Context-Aware, context-awareness, conversational agent, Conversational Agents, Divergents, Language Model, Large-language model, large-language models, Metaverse, Metaverses, Model-based OPC, Onboarding, User interfaces, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}