AHCI RESEARCH GROUP

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

OUR RESEARCH

Scientific Publications

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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}

}