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Ryo Suzuki

4 papers hereh-index 473 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.HC4
same name
  • Ryo Suzuki — 4 papers, h 2
  • Ryo Suzuki — 3 papers, h 0
  • Ryo Suzuki — 3 papers, h 3
  • Ryo Suzuki — 1 paper, h 2
  • Ryo Suzuki — 1 paper, h 25
  • Ryo Suzuki — 1 paper, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.HC2025

Guided Reality: Generating Visually-Enriched AR Task Guidance with LLMs and Vision Models

Ada Yi Zhao, Aditya Gunturu, Ellen Yi-Luen Do +1

Large language models (LLMs) have enabled the automatic generation of step-by-step augmented reality (AR) instructions for a wide range of physical tasks. However, existing LLM-bas…

cs.HC2025

RealitySummary: Exploring On-Demand Mixed Reality Text Summarization and Question Answering using Large Language Models

Aditya Gunturu, Shivesh Jadon, Nandi Zhang +4

Large Language Models (LLMs) are gaining popularity as reading and summarization aids. However, little is known about their potential benefits when integrated with mixed reality (M…

cs.HC2025

MapStory: Prototyping Editable Map Animations with LLM Agents

Aditya Gunturu, Ben Pearman, Keiichi Ihara +4

We introduce MapStory, an LLM-powered animation prototyping tool that generates editable map animation sequences directly from natural language text by leveraging a dual-agent LLM…

cs.HC2025

From Following to Understanding: Investigating the Role of Reflective Prompts in AR-Guided Tasks to Promote Task Understanding

Nandi Zhang, Yukang Yan, Ryo Suzuki

Augmented Reality (AR) is a promising medium for guiding users through tasks, yet its impact on fostering deeper task understanding remains underexplored. This paper investigates t…

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