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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2025

Shi, J.; Jain, R.; Chi, S.; Doh, H.; Chi, H. -G.; Quinn, A. J.; Ramani, K.

CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence Proceedings Article

In: Conf Hum Fact Comput Syst Proc, Association for Computing Machinery, 2025, ISBN: 979-840071394-1 (ISBN).

Abstract | Links | BibTeX | Tags: 'current, Application scenario, AR application, Augmented Reality, Context-Aware, Contextual information, Generative adversarial networks, generative artificial intelligence, Humanoid avatars, In-situ learning, Learning experiences, Power

@inproceedings{shi_caring-ai_2025,

title = {CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence},

author = {J. Shi and R. Jain and S. Chi and H. Doh and H. -G. Chi and A. J. Quinn and K. Ramani},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005725461&doi=10.1145%2f3706598.3713348&partnerID=40&md5=e88afd8426e020155599ef3b2a044774},

doi = {10.1145/3706598.3713348},

isbn = {979-840071394-1 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Conf Hum Fact Comput Syst Proc},

publisher = {Association for Computing Machinery},

abstract = {Context-aware AR instruction enables adaptive and in-situ learning experiences. However, hardware limitations and expertise requirements constrain the creation of such instructions. With recent developments in Generative Artificial Intelligence (Gen-AI), current research tries to tackle these constraints by deploying AI-generated content (AIGC) in AR applications. However, our preliminary study with six AR practitioners revealed that the current AIGC lacks contextual information to adapt to varying application scenarios and is therefore limited in authoring. To utilize the strong generative power of GenAI to ease the authoring of AR instruction while capturing the context, we developed CARING-AI, an AR system to author context-aware humanoid-avatar-based instructions with GenAI. By navigating in the environment, users naturally provide contextual information to generate humanoid-avatar animation as AR instructions that blend in the context spatially and temporally. We showcased three application scenarios of CARING-AI: Asynchronous Instructions, Remote Instructions, and Ad Hoc Instructions based on a design space of AIGC in AR Instructions. With two user studies (N=12), we assessed the system usability of CARING-AI and demonstrated the easiness and effectiveness of authoring with Gen-AI. © 2025 Copyright held by the owner/author(s).},

keywords = {'current, Application scenario, AR application, Augmented Reality, Context-Aware, Contextual information, Generative adversarial networks, generative artificial intelligence, Humanoid avatars, In-situ learning, Learning experiences, Power},

pubstate = {published},

tppubtype = {inproceedings}

}