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Zhongyi Zhou

Zhongyi Zhou has 2 papers in our library, in 2026, most of them on Vision & language; often with Ding Xia, Fan Gao, Haoyu Zhang.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 7 · 40 works · 166 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #14141

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓The University of TokyoTokyo · Japan2019–2026 · 17 paperscurrent🎓East China Normal UniversityShanghai · China2024–2026 · 3 paperscurrent🏢GoogleMountain View · United States2023–2026 · 2 paperscurrent🔬RIKENWako · Japan2026 · 1 papercurrent🔬RIKEN Center for Advanced Intelligence ProjectTokyo · Japan2026 · 1 papercurrent🏢Robotics ResearchCincinnati · United States2026 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workHuman-Computer Interaction · 1 workInformation Systems · 1 work

🧭 Topics 1Research subjects and languages the work is about.Vision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers (2026)
    Automated vehicles cannot rely on driver gestures, so external Human-Machine Interfaces (eHMIs) such as lightbars, mechanical eyes, or robotic arms must signal intent to pedestrians and other road users.
  2. ToolGrad: Efficient Tool-use Dataset Generation with Textual “Gradients” (2026)
    Training LLMs to call tools requires pairs of user requests and correct tool-call sequences. Earlier synthetic pipelines such as ToolBench start from an invented query and then search for a solution with DFS. This search is costly and often fails, and it can leave unsolvable queries or flawed traces in the data.…

 Co-authors here

3 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/zhongyi-zhou/