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Yongqi Zhang

Yongqi Zhang has 2 papers in our library, in 2026, most of them on Information retrieval & search; often with Lei Chen.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 16 · 86 works · 1,210 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #14076

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 Hong Kong University of Science and Technology (Guangzhou)Guangzhou · China2023–2026 · 46 paperscurrent🎓Hong Kong University of Science and TechnologyHong Kong · China2018–2026 · 10 papers🏢4ThparadigmBeijing2020–2023 · 8 papers🎓Shanghai Jiao Tong UniversityShanghai · China2015 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 6The 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 workInformation Systems · 1 work

🧭 Topics 1Research subjects and languages the work is about.Information retrieval & search · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. BubbleRAG: Interactive Cognitive Offloading with Thought Bubble in Retrieval-Augmented Generation (2026)
    Standard retrieval-augmented generation feeds all retrieved documents to an LLM in one pass. The model must find relevant evidence, ignore noise and hold intermediate conclusions in memory without interacting with the text, which leads to problems like "lost-in-the-middle." BubbleRAG takes inspiration from how people…
  2. EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios (2026)
    Small and medium-sized enterprises (SMEs) struggle to align proprietary LLM agents. They have little curated data, tight GPU budgets, fragmented tool ecosystems, and cannot afford separate reward models or pair-wise preference datasets. EfficientTool tackles this with a closed loop of three pipelines:

 Co-authors here

1 co-author 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/yongqi-zhang/