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Seoyeon Eom

dblp:433/0939 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0006-9700-2011ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Accessibility and assistive technology · 77% Human-AI interaction · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Accessibility and assistive technology
assistive technology for visual impairment
1.012026
Toward Independent Online Shopping of the Visually Impaired Through Voice-based Computer-Using Agent · CHI 2026
Human-AI interaction › GUI agent
computer use agents
0.312026
Toward Independent Online Shopping of the Visually Impaired Through Voice-based Computer-Using Agent · CHI 2026

Methods — techniques the papers use, named apart from their topics

wizard-of-oz study · 1.0qualitative interviews · 1.0
YearPublicationVenuePosition
2026 Toward Independent Online Shopping of the Visually Impaired Through Voice-based Computer-Using Agent
abstract
Visually impaired individuals face barriers in online shopping because product details are often conveyed through images, and alternative text is frequently insufficient. The recent advent of Computer-Using Agents (CUA) based on Large Multimodal Models, which can directly manipulate graphical user interfaces, offers new opportunities for such accessibility. However, there is a lack of research that considers how voice-based systems should be designed to support visually impaired users in complex online shopping contexts. Thus, our study qualitatively explores the experiences and needs of visually impaired users as they shop online through voice interaction with a CUA We conducted a Semi-Automatic Wizard-of-Oz study with 12 visually impaired participants, in which they performed shopping tasks with a voice-based CUA system, followed by debriefing interviews. This paper proposes design implications for creating a more inclusive and disability-centered online shopping environment with voice-based CUA for visually impaired users.
Subin Shin, Jeesun Oh, Seoyeon Eom, Sangwon Lee 0012
CHI4