--- title: "Hongfei Yan — author profile and papers — Elamur Research" description: "Hongfei Yan, Hebei Agricultural University: 2 papers on Elamur Research (2026), h-index 10 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/hongfei-yan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hongfei-yan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Hongfei Yan # Hongfei Yan Hongfei Yan has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/); often with [Can Ren](https://md.research.elamur.ai/free/en/authors/can-ren/), [Chengying Tu](https://md.research.elamur.ai/free/en/authors/chengying-tu/), [Jingang Wang](https://md.research.elamur.ai/free/en/authors/jingang-wang/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5100934344) · [**h-index 10**](https://openalex.org/authors/A5100934344) · [34 works](https://openalex.org/works?filter=author.id:A5100934344) · [347 citations](https://openalex.org/works?filter=author.id:A5100934344&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/hongfei-yan/#papers) · [⭐ Paper Stars ranking: #13607](https://md.research.elamur.ai/free/en/paper-stars/page/137/#star-13607) 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=Hongfei+Yan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Hongfei+Yan) · [dblp](https://dblp.org/search?q=Hongfei+Yan) · [ACL Anthology](https://aclanthology.org/search/?q=Hongfei+Yan) ## Affiliations [🎓**Hebei Agricultural University** Baoding · China 2022–2026 · 8 papers*current*](https://ror.org/009fw8j44) · [🎓**Peking University** Beijing · China 2005–2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/peking-university/) · [🎓**Nanjing Tech University** Nanjing · China 2023–2026 · 3 papers*current*](https://ror.org/03sd35x91) · [🏛️**Hunan Entry-Exit Inspection and Quarantine Bureau** Changsha · China 2009–2013 · 6 papers](https://ror.org/03ty5px05) · [🏢**Alibaba Group** Hangzhou · China 2024–2025 · 2 papers](https://md.research.elamur.ai/free/en/companies/alibaba-group/) 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 5 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [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 · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/hongfei-yan/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/)** *(2026)* Mid-training large language models often relies on synthetic question–answer data. However, existing generators mostly reformat source text into simple, uniform QA pairs, which limits both volume and variety. The authors present BoostQA, a pipeline that first diagnoses what a pre-trained model lacks and then… 2. **[LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points](https://md.research.elamur.ai/free/en/papers/zhang-2026-linkqa-synthesizing-diverse-qa-multiple/)** *(2026)* Training LLMs is increasingly limited by a shortage of diverse, high-quality data, especially across many academic disciplines. ## Co-authors here 6 co-authors with a page, the most papers together first. - [Can Ren](https://md.research.elamur.ai/free/en/authors/can-ren/) ×2 - [Chengying Tu](https://md.research.elamur.ai/free/en/authors/chengying-tu/) ×2 - [Jingang Wang](https://md.research.elamur.ai/free/en/authors/jingang-wang/) ×2 - [Rongxiang Weng](https://md.research.elamur.ai/free/en/authors/rongxiang-weng/) ×2 - [Xuemiao Zhang](https://md.research.elamur.ai/free/en/authors/xuemiao-zhang/) ×2 - [Xunliang Cai](https://md.research.elamur.ai/free/en/authors/xunliang-cai/) ×2 ## 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 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) Updated 2 November 2026