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Zhiqi Shen

4 papers hereh-index 349 citations14 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.AI1
  • cs.HC1
same name
  • Zhiqi Shen — 8 papers
  • Zhiqi Shen — 7 papers
  • Zhiqi Shen — 5 papers, h 37
  • Zhiqi Shen — 5 papers, h 4
  • Zhiqi Shen — 4 papers, h 3
  • Zhiqi Shen — 4 papers, h 2

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

most citedEchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

Hand2World: Autoregressive Egocentric Interaction Generation via Free-Space Hand Gestures

Yuxi Wang, Wenqi Ouyang, Tianyi Wei +3

Egocentric interactive world models are essential for augmented reality and embodied AI, where visual generation must respond to user input with low latency, geometric consistency,…

cs.HC2025

An Efficient Interaction Human-AI Synergy System Bridging Visual Awareness and Large Language Model for Intensive Care Units

Yibowen Zhao, Yiming Cao, Zhiqi Shen +4

Intensive Care Units (ICUs) are critical environments characterized by high-stakes monitoring and complex data management. However, current practices often rely on manual data tran…

cs.CV2025★ 1 cited

EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models

Botai Yuan, Yutian Zhou, Yingjie Wang +9

Recent benchmarks for medical Large Vision-Language Models (LVLMs) emphasize leaderboard accuracy, overlooking reliability and safety. We study sycophancy -- models' tendency to un…

cs.AI2025

Modeling Human Responses to Multimodal AI Content

Zhiqi Shen, Shaojing Fan, Danni Xu +2

As AI-generated content becomes widespread, so does the risk of misinformation. While prior research has primarily focused on identifying whether content is authentic, much less is…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.