--- title: "Yunhui Liu · Nanjing University — author profile and papers" description: "Yunhui Liu, Nanjing University: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yunhui-liu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yunhui-liu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yunhui Liu # Yunhui Liu Yunhui Liu 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/), [Knowledge graphs & ontologies](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Hongru Sun](https://md.research.elamur.ai/free/en/authors/hongru-sun/), [Jun Xu](https://md.research.elamur.ai/free/en/authors/jun-xu/), [Junyu Luo](https://md.research.elamur.ai/free/en/authors/junyu-luo/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5129700445) · [**h-index 1**](https://openalex.org/authors/A5129700445) · [11 works](https://openalex.org/works?filter=author.id:A5129700445) · [2 citations](https://openalex.org/works?filter=author.id:A5129700445&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yunhui-liu/#papers) · [⭐ Paper Stars ranking: #14096](https://md.research.elamur.ai/free/en/paper-stars/page/141/#star-14096) 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=Yunhui+Liu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yunhui+Liu) · [dblp](https://dblp.org/search?q=Yunhui+Liu) · [ACL Anthology](https://aclanthology.org/search/?q=Yunhui+Liu) ## Affiliations [🎓**Nanjing University** Nanjing · China 2026 · 11 papers*current*](https://md.research.elamur.ai/free/en/universities/nanjing-university/) 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 4 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/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 3 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Knowledge graphs & ontologies · 1 work](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/yunhui-liu/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/)** *(2026)* RL-based post-training is now a leading way to strengthen reasoning in LLMs, but it is held back by data scarcity in two forms. 2. **[GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion](https://md.research.elamur.ai/free/en/papers/xie-2026-gs-quant-granular-semantic-generative/)** *(2026)* Knowledge graph completion (KGC) with LLMs faces a mismatch: graph embeddings are dense continuous vectors, while LLMs reason over discrete token sequences. ## Co-authors here 12 co-authors with a page, the most papers together first. - [Hongru Sun](https://md.research.elamur.ai/free/en/authors/hongru-sun/) - [Jun Xu](https://md.research.elamur.ai/free/en/authors/jun-xu/) - [Junyu Luo](https://md.research.elamur.ai/free/en/authors/junyu-luo/) - [Ming Zhang](https://md.research.elamur.ai/free/en/authors/ming-zhang/) - [Qianzi Hou](https://md.research.elamur.ai/free/en/authors/qianzi-hou/) - [Qizhuo Xie](https://md.research.elamur.ai/free/en/authors/qizhuo-xie/) - [Tao Zheng](https://md.research.elamur.ai/free/en/authors/tao-zheng/) - [Tieke He](https://md.research.elamur.ai/free/en/authors/tieke-he/) - [Xing Wei](https://md.research.elamur.ai/free/en/authors/xing-wei/) - [Yatao Bian](https://md.research.elamur.ai/free/en/authors/yatao-bian/) - [Yuchen Mou](https://md.research.elamur.ai/free/en/authors/yuchen-mou/) - [Zhiyin Yu](https://md.research.elamur.ai/free/en/authors/zhiyin-yu/) ## 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 Updated 2 November 2026