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Xiaowei Yuan

Xiaowei Yuan has 2 papers in our library, in 2026, most of them on Reasoning, Information retrieval & search; often with Jun Zhao, Kang Liu, Ziyang Huang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 3 · 9 works · 27 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #14014

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

🎓Jinan UniversityGuangzhou · China2022–2026 · 4 paperscurrent🏛️Chinese Academy of SciencesBeijing · China2026 · 1 papercurrent🔬Institute of AutomationBeijing · China2026 · 1 papercurrent🎓University of Chinese Academy of SciencesBeijing · China2026 · 1 papercurrent🎓Qufu Normal UniversityQufu · China2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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 worksInformation Systems · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 2 worksInformation retrieval & search · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts (2026)
    Retrieval-augmented generation (RAG) works well when the retrieved passages are clean. Accuracy drops sharply when the passages are noisy, outdated or contradict each other. The authors study whether a model's own knowledge can act as a reference point for judging such evidence.
  2. R\textthreesuperiorA: Reinforced Reasoning for Relevance Assessment for RAG in User-Generated Content Platforms (2026)
    The paper addresses query–document relevance judgment for retrieval-augmented generation on user-generated content (UGC) platforms.

 Co-authors here

8 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

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