--- title: "Jiayi Yuan — author profile and papers" description: "Jiayi Yuan, University of Leeds: 2 papers on Elamur Research (2024–2025), h-index 15 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/jiayi-yuan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jiayi-yuan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Jiayi Yuan # Jiayi Yuan 2 papers on this site · 2024–2025 current affiliation [University of Leeds](https://ror.org/024mrxd33), Leeds, United Kingdom Jiayi Yuan has 2 papers on this site, in 2024–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Shaochen Zhong](https://md.research.elamur.ai/free/en/authors/shaochen-zhong/), [Xia Hu](https://md.research.elamur.ai/free/en/authors/xia-hu/), [Beidi Chen](https://md.research.elamur.ai/free/en/authors/beidi-chen/). [OpenAlex](https://openalex.org/A5100309335) · [ORCID](https://orcid.org/0000-0001-8315-7609) · [**h-index 15**](https://openalex.org/authors/A5100309335) · [69 works](https://openalex.org/works?filter=author.id:A5100309335) · [691 citations](https://openalex.org/works?filter=author.id:A5100309335&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [2 works on this site](https://md.research.elamur.ai/free/en/authors/jiayi-yuan/#papers) · [387 citations in our library](https://md.research.elamur.ai/free/en/authors/jiayi-yuan/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=Jiayi+Yuan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Jiayi+Yuan) · [dblp](https://dblp.org/search?q=Jiayi+Yuan) · [ACL Anthology](https://aclanthology.org/search/?q=Jiayi+Yuan) ## Affiliations - [University of Leeds](https://ror.org/024mrxd33) · Leeds, United Kingdom —current · 2023–2026 on 6 papers - [Beijing Normal University](https://ror.org/022k4wk35) · Beijing, China —2022–2025 on 7 papers - [Rice University](https://ror.org/008zs3103) · Houston, United States —2022–2025 on 6 papers - [Mianyang Normal University](https://ror.org/02rka3n91) · Mianyang, China —2024–2025 on 4 papers - [Nanjing Tech University](https://ror.org/03sd35x91) · Nanjing, China —2025 on 3 papers - [State Key Laboratory of Materials-Oriented Chemical Engineering](https://ror.org/00s0wpd42) · Nanjing —2025 on 3 papers - [Southeast University](https://ror.org/04ct4d772) · Nanjing, China —2020–2024 on 5 papers - [Wenzhou Institute, University of Chinese Academy of Sciences](https://ror.org/004vy8c88) · Wenzhou, China —2023–2024 on 2 papers - [Harbin University of Commerce](https://ror.org/03zsxkw25) · Harbin, China —2020–2023 on 3 papers - [Nanjing Agricultural University](https://ror.org/05td3s095) · Nanjing, China —2022–2023 on 2 papers From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 23 more institutions on single bylines are not listed. ## Topics [Language models & pretraining 1](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning 1](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Efficient models & compression 1](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Papers The most cited first (OpenAlex and our library). 1. **[KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/)** *(2024 · 243 citations)* Serving LLMs cheaply means batching many requests. With large batches and long contexts, though, the KV cache becomes the main memory and speed bottleneck: it can exceed the size of the model weights, and the GPU must read it in full for every generated token. The authors examine how values are distributed inside the… 2. **[Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)** *(2025 · 153 citations)* Reasoning-focused LLMs such as OpenAI o1 and DeepSeek-R1 get better at math and coding by writing long Chain-of-Thought traces. ## Co-authors here 7 co-authors with a page, the most papers together first. - [Shaochen Zhong](https://md.research.elamur.ai/free/en/authors/shaochen-zhong/) ×2 - [Xia Hu](https://md.research.elamur.ai/free/en/authors/xia-hu/) ×2 - [Beidi Chen](https://md.research.elamur.ai/free/en/authors/beidi-chen/) - [Hanjie Chen](https://md.research.elamur.ai/free/en/authors/hanjie-chen/) - [Hongye Jin](https://md.research.elamur.ai/free/en/authors/hongye-jin/) - [Hongyi Liu](https://md.research.elamur.ai/free/en/authors/hongyi-liu/) - [Tianyi Zhang](https://md.research.elamur.ai/free/en/authors/tianyi-zhang/) ## Cited by Papers of our library cite their works 387 times (of the 140 884 papers whose bibliographies we read); [8 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jiayi-yuan/cited-by/).