--- title: "Weihong Zhong — author profile and papers — Elamur Research" description: "Weihong Zhong: 2 papers on Elamur Research (2023–2025) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/weihong-zhong/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/weihong-zhong/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Weihong Zhong # Weihong Zhong Weihong Zhong has 2 papers in our library, in 2023–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/); often with [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/), [Lei Huang](https://md.research.elamur.ai/free/en/authors/lei-huang/), [Weitao Ma](https://md.research.elamur.ai/free/en/authors/weitao-ma/). 2 papers in our library · 2023–2025 No OpenAlex profile matched yet. [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/weihong-zhong/#papers) · [🔗 Cited 861 times in our library](https://md.research.elamur.ai/free/en/authors/weihong-zhong/cited-by/) · [⭐ Paper Stars ranking: #999](https://md.research.elamur.ai/free/en/paper-stars/page/10/#star-999) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Weihong+Zhong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Weihong+Zhong) · [dblp](https://dblp.org/search?q=Weihong+Zhong) · [ACL Anthology](https://aclanthology.org/search/?q=Weihong+Zhong) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) 💡 Concepts 3 Key ideas and methods explained on our concept pages.[Chatbots · 1 work](https://md.research.elamur.ai/free/en/concepts/chatbot/) · [Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) · [Large language models · 1 work](https://md.research.elamur.ai/free/en/concepts/large-language-models/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/weihong-zhong/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/weihong-zhong/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)** *(2023 · 3,231 citations)* Large language models often produce fluent, convincing text that is not supported by facts or by the input they were given. 2. **[Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization](https://md.research.elamur.ai/free/en/papers/huang-2025-improving-contextual-faithfulness-large-language/)** *(2025 · 11 citations)* The paper addresses faithfulness hallucination in retrieval-augmented long-form question answering (LFQA), where a model writes paragraph-length answers containing claims that the retrieved documents do not support or that contradict them. ## Co-authors here 12 of 16 co-authors with a page, the most papers together first. - [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/) ×2 - [Lei Huang](https://md.research.elamur.ai/free/en/authors/lei-huang/) ×2 - [Weitao Ma](https://md.research.elamur.ai/free/en/authors/weitao-ma/) ×2 - [Xiaocheng Feng](https://md.research.elamur.ai/free/en/authors/xiaocheng-feng/) ×2 - [Baoxin Wang](https://md.research.elamur.ai/free/en/authors/baoxin-wang/) - [Dayong Wu](https://md.research.elamur.ai/free/en/authors/dayong-wu/) - [Guoping Hu](https://md.research.elamur.ai/free/en/authors/guoping-hu/) - [Haotian Wang](https://md.research.elamur.ai/free/en/authors/haotian-wang/) - [Qianglong Chen](https://md.research.elamur.ai/free/en/authors/qianglong-chen/) - [Ting Liu](https://md.research.elamur.ai/free/en/authors/ting-liu/) - [Weihua Peng](https://md.research.elamur.ai/free/en/authors/weihua-peng/) - [Xiachong Feng](https://md.research.elamur.ai/free/en/authors/xiachong-feng/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/): [ACM Transactions on Information Systems 2023](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/2023/) ## Cited by Papers of our library cite their works 861 times (of the 149,439 papers whose bibliographies we read); [172 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/weihong-zhong/cited-by/). Updated 1 November 2026