--- title: "Mingxuan Yuan — author profile and papers — Elamur Research" description: "Mingxuan Yuan, Huawei Technologies: 3 papers on Elamur Research (2026), h-index 26 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/mingxuan-yuan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/mingxuan-yuan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Mingxuan Yuan # Mingxuan Yuan Mingxuan Yuan has 3 papers in our library, in 2026, most of them on [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Hui-Ling Zhen](https://md.research.elamur.ai/free/en/authors/hui-ling-zhen/), [Xianzhi Yu](https://md.research.elamur.ai/free/en/authors/xianzhi-yu/), [Pengxiang Zhao](https://md.research.elamur.ai/free/en/authors/pengxiang-zhao/). 3 papers in our library · 2026 [OpenAlex](https://openalex.org/A5078949174) · [ORCID](https://orcid.org/0000-0002-2236-8784) · [Wikidata](https://www.wikidata.org/wiki/Q130836243) · [**h-index 26**](https://openalex.org/authors/A5078949174) · [191 works](https://openalex.org/works?filter=author.id:A5078949174) · [2,270 citations](https://openalex.org/works?filter=author.id:A5078949174&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/mingxuan-yuan/#papers) · 🔗 Cited 1 time in our library · [⭐ Paper Stars ranking: #11077](https://md.research.elamur.ai/free/en/paper-stars/page/111/#star-11077) 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=Mingxuan+Yuan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Mingxuan+Yuan) · [dblp](https://dblp.org/search?q=Mingxuan+Yuan) · [ACL Anthology](https://aclanthology.org/search/?q=Mingxuan+Yuan) ## Affiliations [🏢**Huawei Technologies** Shenzhen · China 2012–2026 · 167 papers*current*](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) · [🎓**Hong Kong University of Science and Technology** Hong Kong · China 2007–2016 · 23 papers](https://md.research.elamur.ai/free/en/universities/hong-kong-university-of-science-and-technology/) · [🏢**Huawei Technologies** Stockholm · Sweden 2024–2026 · 7 papers](https://ror.org/0500fyd17) · [🎓**City University of Hong Kong** Hong Kong · China 2023–2026 · 4 papers](https://md.research.elamur.ai/free/en/universities/city-university-of-hong-kong/) · [🎓**Nanjing University** Nanjing · China 2025 · 4 papers](https://md.research.elamur.ai/free/en/universities/nanjing-university/) · [🎓**Chinese University of Hong Kong** Hong Kong · China 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong/) 🏛️**Huawei Noah's Ark Lab** Hong Kong · [China](https://md.research.elamur.ai/free/en/countries/china/) Employment From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 3 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/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Electrical and Electronic Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/) 🧭 Topics 1 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/mingxuan-yuan/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis](https://md.research.elamur.ai/free/en/papers/pei-2026-analytical-ffn-moe-restructuring-activation/)** *(2026 · 1 citation)* Most inference compute in large language models goes to the feed-forward (FFN) blocks. Converting a dense model into a Mixture-of-Experts (MoE) can cut that cost, but earlier conversion methods needed continual training on billions of tokens. Pei et al. instead restructure FFNs after training, in a single analytical… 2. **[Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats](https://md.research.elamur.ai/free/en/papers/zhao-2026-unleashing-low-bit-inference-ascend/)** *(2026 · 1 citation)* The paper asks whether Huawei's HiFloat number formats, built for Ascend NPUs, work well for post-training quantization (PTQ) of large language models. 3. **[RIFT: Repurposing Negative Samples via Reward-Informed Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-rift-repurposing-negative-samples-reward/)** *(2026)* Post-training LLMs with Supervised Fine-Tuning requires expensive expert demonstrations. Rejection Sampling Fine-Tuning (RFT) avoids this by training on the model's own verified outputs, but it throws away every incorrect sample, which wastes compute and ignores information about failure modes. The authors propose… ## Co-authors here 6 co-authors with a page, the most papers together first. - [Hui-Ling Zhen](https://md.research.elamur.ai/free/en/authors/hui-ling-zhen/) ×2 - [Xianzhi Yu](https://md.research.elamur.ai/free/en/authors/xianzhi-yu/) ×2 - [Pengxiang Zhao](https://md.research.elamur.ai/free/en/authors/pengxiang-zhao/) - [Sinno Jialin Pan](https://md.research.elamur.ai/free/en/authors/sinno-jialin-pan/) - [Xin Wang](https://md.research.elamur.ai/free/en/authors/xin-wang/) - [Xing Li](https://md.research.elamur.ai/free/en/authors/xing-li/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2 - [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/) ## Cited by Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read). Updated 1 November 2026