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Qinggang Zhang

Qinggang Zhang has 4 papers in our library, in 2025–2026, most of them on Information retrieval & search, Language models & pretraining, Reasoning; often with Yilin Xiao, Chuang Zhou, Xiao Xia Huang.

4 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 12 · 43 works · 319 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 70 times in our library · ⭐ Paper Stars ranking: #6808

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

🎓Hong Kong Polytechnic UniversityHong Kong · China2022–2026 · 23 paperscurrent🎓Jilin UniversityChangchun · China2026 · 6 papersEmployment since 2026 · Professor, School of Artificial Intelligencecurrent🎓Wuhan UniversityWuhan · China2026 · 1 papercurrent
🏛️The Hong Kong Polytechnic University Faculty of EngineeringHong Kong · China2021–2025Education 2021–2025

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).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksInformation Systems · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 3Research subjects and languages the work is about.Information retrieval & search · 4 worksLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20253 papers

 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. FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation (2025 · 27 citations)
    Retrieval-augmented LLMs often fail to stay faithful to retrieved passages when those passages contradict what the model learned during pre-training.
  3. You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structures (2025 · 9 citations)
    Graph-based RAG systems such as Microsoft GraphRAG, HippoRAG, RAPTOR, LightRAG and KGP first convert the entire corpus into a graph.
  4. LogicPoison: Logical Attacks on Graph Retrieval-Augmented Generation (2026 · 1 citation)
    GraphRAG systems answer questions by reasoning over a knowledge graph built from a text corpus. They tend to resist classic RAG attacks for three reasons: injected documents end up isolated in the graph, embedded instructions are lost when text becomes entity–relation structures, and redundant paths compensate for…

 Co-authors here

12 of 13 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 70 times (of the 149,439 papers whose bibliographies we read); 14 citing papers with a page here →.

Updated

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