Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision People

Fuente: arXiv
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Auteurs principaux: Collins, Jazmin, Lin, Sharon Y, Liu, Tianqi, Won, Andrea Stevenson, Azenkot, Shiri
Format: Preprint
Publié: 2026
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author Collins, Jazmin
Lin, Sharon Y
Liu, Tianqi
Won, Andrea Stevenson
Azenkot, Shiri
author_facet Collins, Jazmin
Lin, Sharon Y
Liu, Tianqi
Won, Andrea Stevenson
Azenkot, Shiri
contents As social virtual reality (VR) grows more popular, addressing accessibility for blind and low vision (BLV) users is increasingly critical. Researchers have proposed an AI "sighted guide" to help users navigate VR and answer their questions, but it has not been studied with users. To address this gap, we developed a large language model (LLM)-powered guide and studied its use with 16 BLV participants in virtual environments with confederates posing as other users. We found that when alone, participants treated the guide as a tool, but treated it companionably around others, giving it nicknames, rationalizing its mistakes with its appearance, and encouraging confederate-guide interaction. Our work furthers understanding of guides as a versatile method for VR accessibility and presents design recommendations for future guides.
format Preprint
id arxiv_https___arxiv_org_abs_2603_09964
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision People
Collins, Jazmin
Lin, Sharon Y
Liu, Tianqi
Won, Andrea Stevenson
Azenkot, Shiri
Human-Computer Interaction
Artificial Intelligence
Emerging Technologies
H.5.1; K.4.2; I.2.1
As social virtual reality (VR) grows more popular, addressing accessibility for blind and low vision (BLV) users is increasingly critical. Researchers have proposed an AI "sighted guide" to help users navigate VR and answer their questions, but it has not been studied with users. To address this gap, we developed a large language model (LLM)-powered guide and studied its use with 16 BLV participants in virtual environments with confederates posing as other users. We found that when alone, participants treated the guide as a tool, but treated it companionably around others, giving it nicknames, rationalizing its mistakes with its appearance, and encouraging confederate-guide interaction. Our work furthers understanding of guides as a versatile method for VR accessibility and presents design recommendations for future guides.
title Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision People
topic Human-Computer Interaction
Artificial Intelligence
Emerging Technologies
H.5.1; K.4.2; I.2.1
url https://arxiv.org/abs/2603.09964