--- title: "Yuhui Li — author profile and papers" description: "Yuhui Li, Hunan University: 2 papers on Elamur Research (2024), h-index 8 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yuhui-li/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yuhui-li/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yuhui Li # Yuhui Li 2 papers on this site · 2024 current affiliation [Hunan University](https://ror.org/05htk5m33), Changsha, China; [Harbin Institute of Technology](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/), Harbin, China Yuhui Li has 2 papers on this site, in 2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Chao Zhang](https://md.research.elamur.ai/free/en/authors/chao-zhang/), [Fangyun Wei](https://md.research.elamur.ai/free/en/authors/fangyun-wei/), [Hongyang Zhang](https://md.research.elamur.ai/free/en/authors/hongyang-zhang/). [OpenAlex](https://openalex.org/A5100688624) · [ORCID](https://orcid.org/0000-0003-3375-0273) · [**h-index 8**](https://openalex.org/authors/A5100688624) · [50 works](https://openalex.org/works?filter=author.id:A5100688624) · [302 citations](https://openalex.org/works?filter=author.id:A5100688624&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [2 works on this site](https://md.research.elamur.ai/free/en/authors/yuhui-li/#papers) · [295 citations in our library](https://md.research.elamur.ai/free/en/authors/yuhui-li/cited-by/) 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=Yuhui+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yuhui+Li) · [dblp](https://dblp.org/search?q=Yuhui+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Yuhui+Li) ## Affiliations - [Hunan University](https://ror.org/05htk5m33) · Changsha, China —current · 2022–2025 on 8 papers - [Harbin Institute of Technology](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) · Harbin, China —current · 2025 on 1 paper - [Peking University](https://md.research.elamur.ai/free/en/universities/peking-university/) · Beijing, China —2024 on 2 papers - [Shantou University](https://ror.org/01a099706) · Shantou, China —2020–2023 on 4 papers - [Chongqing University of Posts and Telecommunications](https://ror.org/03dgaqz26) · Chongqing, China —2022–2023 on 2 papers - [University of Electronic Science and Technology of China](https://md.research.elamur.ai/free/en/universities/university-of-electronic-science-and-technology-of-china/) · Chengdu, China —2020–2022 on 2 papers - [South China Normal University](https://ror.org/01kq0pv72) · Guangzhou, China —2020–2021 on 5 papers - [Henan Normal University](https://ror.org/00s13br28) · Xinxiang, China —2016 on 2 papers - [Kunming University of Science and Technology](https://ror.org/00xyeez13) · Kunming, China —2002–2015 on 5 papers - [Huaihua University](https://ror.org/04zn6xq74) · Huaihua, China —2007–2008 on 2 papers From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 more institutions on single bylines are not listed. ## Topics [Language models & pretraining 1](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/yuhui-li/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)** *(2024 · 204 citations)* Generating text token by token makes LLM inference slow. Speculative sampling speeds it up by letting a cheap model propose several tokens that the full model then checks in a single pass. However, good draft models are hard to find, especially for the smallest model in a family. EAGLE replaces the separate draft… 2. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/)** *(2024 · 131 citations)* Speculative sampling makes LLM inference faster: a cheap draft model proposes tokens, and the original model checks them in parallel. ## Co-authors here 3 co-authors with a page, the most papers together first. - [Chao Zhang](https://md.research.elamur.ai/free/en/authors/chao-zhang/) ×2 - [Fangyun Wei](https://md.research.elamur.ai/free/en/authors/fangyun-wei/) ×2 - [Hongyang Zhang](https://md.research.elamur.ai/free/en/authors/hongyang-zhang/) ×2 ## Cited by Papers of our library cite their works 295 times (of the 140 884 papers whose bibliographies we read); [3 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yuhui-li/cited-by/).