--- title: "Runming Yang — author profile and papers — Elamur Research" description: "Runming Yang, University of Hong Kong: 4 papers on Elamur Research (2025–2026), h-index 0 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/runming-yang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/runming-yang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Runming Yang # Runming Yang Runming Yang has 4 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Ngai Wong](https://md.research.elamur.ai/free/en/authors/ngai-wong/), [Taiqiang Wu](https://md.research.elamur.ai/free/en/authors/taiqiang-wu/), [Jiahao Wang](https://md.research.elamur.ai/free/en/authors/jiahao-wang/). 4 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5139782143) · [**h-index 0**](https://openalex.org/authors/A5139782143) · [2 works](https://openalex.org/works?filter=author.id:A5139782143) · [0 citations](https://openalex.org/works?filter=author.id:A5139782143&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/runming-yang/#papers) · [🔗 Cited 59 times in our library](https://md.research.elamur.ai/free/en/authors/runming-yang/cited-by/) · [⭐ Paper Stars ranking: #7490](https://md.research.elamur.ai/free/en/paper-stars/page/75/#star-7490) 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=Runming+Yang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Runming+Yang) · [dblp](https://dblp.org/search?q=Runming+Yang) · [ACL Anthology](https://aclanthology.org/search/?q=Runming+Yang) ## Affiliations [🎓**University of Hong Kong** Pok Fu Lam · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-hong-kong/) 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 7 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Electrical and Electronic Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/) 🧭 Topics 3 Research subjects and languages the work is about.[Efficient models & compression · 2 works](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/runming-yang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/runming-yang/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-rethinking-kullback-leibler-divergence-knowledge/)** *(2025 · 47 citations)* Distilling large language models usually means training a student to match the teacher's next-token distribution with a Kullback-Leibler loss. 2. **[Revisiting Model Interpolation for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-revisiting-model-interpolation-efficient-reasoning/)** *(2026 · 6 citations)* The paper looks at efficient reasoning: how to keep the accuracy of long chain-of-thought models while producing fewer tokens. 3. **[Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models](https://md.research.elamur.ai/free/en/papers/xiao-2026-exploring-layer-wise-information-effectiveness/)** *(2026 · 5 citations)* Compressing small language models (under 8B parameters) to about 2 bits per weight usually ruins their accuracy. 4. **[ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token Selection](https://md.research.elamur.ai/free/en/papers/liu-2026-profit-leveraging-high-value-signals/)** *(2026 · 4 citations)* Standard supervised fine-tuning (SFT) trains an LLM to reproduce one reference answer token by token. Valid alternative phrasings are therefore penalized, and the model tends to memorize surface wording. Training on several references per prompt could help, but the authors find it expensive and unstable. They instead… ## Co-authors here 10 co-authors with a page, the most papers together first. - [Ngai Wong](https://md.research.elamur.ai/free/en/authors/ngai-wong/) ×3 - [Taiqiang Wu](https://md.research.elamur.ai/free/en/authors/taiqiang-wu/) ×3 - [Jiahao Wang](https://md.research.elamur.ai/free/en/authors/jiahao-wang/) ×2 - [Tao Liu](https://md.research.elamur.ai/free/en/authors/tao-liu/) ×2 - [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/) - [Junjie Wang](https://md.research.elamur.ai/free/en/authors/junjie-wang/) - [Shaoning Sun](https://md.research.elamur.ai/free/en/authors/shaoning-sun/) - [Yujiu Yang](https://md.research.elamur.ai/free/en/authors/yujiu-yang/) - [Zhe Zhao](https://md.research.elamur.ai/free/en/authors/zhe-zhao/) - [Zunhai Su](https://md.research.elamur.ai/free/en/authors/zunhai-su/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 - [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/) - [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/2025/) ## Cited by Papers of our library cite their works 59 times (of the 149,439 papers whose bibliographies we read); [16 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/runming-yang/cited-by/). Updated 31 October 2026