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Zhongxiang Sun

Zhongxiang Sun has 3 papers in our library, in 2025–2026, most of them on Reasoning, Language models & pretraining, Information retrieval & search; often with Jun Xu, Weijie Yu, Xiao Zhang.

3 papers in our library · 2025–2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 18 times in our library · ⭐ Paper Stars ranking: #8863

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

🎓Renmin University of ChinaBeijing · China2026 · 4 paperscurrent

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 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 2 works

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksInformation retrieval & search · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding (2025 · 22 citations)
    Retrieval-augmented generation (RAG) pipelines still struggle with questions that require several chained reasoning and lookup steps.
  2. Streaming Hallucination Detection in Long Chain-of-Thought Reasoning (2026 · 1 citation)
    Errors in long chain-of-thought (CoT) reasoning tend to appear gradually and spread across steps, often hidden behind locally convincing text.
  3. When Personalization Misleads: Understanding and Mitigating Hallucinations in Personalized LLMs (2026)
    The paper examines an overlooked risk of personalized LLMs. When a model is conditioned on a user's chat history or profile, it may answer factual questions in line with what the user said before instead of with the truth. The authors call this failure "personalization-induced hallucination." They attribute it to…

 Co-authors here

10 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 18 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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