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Junnan Dong

Junnan Dong has 3 papers in our library, in 2025–2026, most of them on Information retrieval & search, Language models & pretraining, Reasoning; often with Chuang Zhou, Xiao Xia Huang, Yilin Xiao.

3 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 11 · 40 works · 280 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 50 times in our library · ⭐ Paper Stars ranking: #8663

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

🏢TencentShenzhen · China2025–2026 · 11 paperscurrent🏥Ruijin HospitalShanghai · China2026 · 1 papercurrent🎓Hong Kong Polytechnic UniversityHong Kong · China2022–2025 · 17 papersEducation 2022–2025 · Ph.D., Department of ComputingEmployment🎓Shaanxi Normal UniversityXi'an · China2018 · 2 papers
🏛️Tencent Youtu LabShanghai · China2025Employment since 2025 · Senior Researcher

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksInformation Systems · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Information retrieval & search · 2 worksLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models (2025 · 64 citations)
    General-purpose LLMs often fall short in specialized fields. Their domain knowledge is shallow, they struggle with long chains of rule-bound reasoning, and they misread terms whose meaning depends on context. Fine-tuning on domain data can introduce hallucinations and catastrophic forgetting. Classic RAG avoids…
  2. Collision to Cognition: Hash-Driven Graph Construction for Efficient RAG (2026)
    GraphRAG systems handle multi-hop questions better than flat dense retrieval, but building their graphs is costly.
  3. Query-Aware Knowledge Retrieval via Hyperbolic Structuring (2026)
    Graph-based retrieval-augmented generation (GraphRAG) usually builds one fixed graph over a corpus, using heuristics like entity co-occurrence or clustering.

 Co-authors here

12 of 14 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 50 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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