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Ying Xiong

Ying Xiong has 2 papers in our library, in 2024–2026, most of them on Reasoning, Information retrieval & search; often with Buzhou Tang, Can Chen, Haolun Wu.

2 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 16 · 99 works · 805 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 17 times in our library · ⭐ Paper Stars ranking: #7052

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

🎓Guangzhou University of Chinese MedicineGuangzhou · China2025–2026 · 7 paperscurrent🎓Hong Kong Polytechnic UniversityHong Kong · China2024–2026 · 3 paperscurrent🎓China University of GeosciencesWuhan · China2025–2026 · 2 paperscurrent🎓Shanghai Jiao Tong UniversityShanghai · China2010–2023 · 15 papers🏥XinHua HospitalShanghai · China2010–2023 · 12 papers🎓Sichuan UniversityChengdu · China2009–2024 · 7 papers🏥West China Second University Hospital of Sichuan UniversityChengdu · China2009–2022 · 5 papers🎓Capital Medical UniversityBeijing · China2008–2021 · 4 papers🔬State Key Laboratory of Oncology in South ChinaGuangzhou2024–2025 · 3 papers🏥Sun Yat-sen University Cancer CenterGuangzhou · China2024–2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 39 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Retrieval-Augmented Generation for Natural Language Processing: A Survey (2024 · 86 citations)
    Large language models store knowledge implicitly in their weights. As a result, they can produce fluent but false answers, they need costly retraining to refresh facts, and they often lack depth in specialised domains. Retrieval-augmented generation (RAG) addresses these issues by consulting an external knowledge…
  2. SR-RAG: Verifiable Multi-Hop Reasoning via On-the-fly Symbolic Graph Construction (2026)
    Multi-hop question answering is still difficult for retrieval-augmented generation. Aggregate-first systems such as GraphRAG build a corpus-wide knowledge graph in advance, which is costly and hard to keep current. Dynamic-first agents such as ReAct alternate retrieval and generation, but one wrong intermediate…

 Co-authors here

7 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.

 Cited by

Papers of our library cite their works 17 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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