--- title: "Yuqiang Li — author profile and papers — Elamur Research" description: "Yuqiang Li, Shanghai Artificial Intelligence Laboratory: 3 papers on Elamur Research (2024–2025), h-index 5 — affiliations, topics, co-authors…" canonical: "https://research.elamur.ai/free/en/authors/yuqiang-li/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yuqiang-li/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yuqiang Li # Yuqiang Li Yuqiang Li has 3 papers in our library, 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/); often with [Dongzhan Zhou](https://md.research.elamur.ai/free/en/authors/dongzhan-zhou/), [Tong Xie](https://md.research.elamur.ai/free/en/authors/tong-xie/), [Wanli Ouyang](https://md.research.elamur.ai/free/en/authors/wanli-ouyang/). 3 papers in our library · 2024–2025 [OpenAlex](https://openalex.org/A5108783365) · [ORCID](https://orcid.org/0000-0002-2243-6038) · [**h-index 5**](https://openalex.org/authors/A5108783365) · [12 works](https://openalex.org/works?filter=author.id:A5108783365) · [103 citations](https://openalex.org/works?filter=author.id:A5108783365&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/yuqiang-li/#papers) · [🔗 Cited 143 times in our library](https://md.research.elamur.ai/free/en/authors/yuqiang-li/cited-by/) · [⭐ Paper Stars ranking: #8170](https://md.research.elamur.ai/free/en/paper-stars/page/82/#star-8170) 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=Yuqiang+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yuqiang+Li) · [dblp](https://dblp.org/search?q=Yuqiang+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Yuqiang+Li) ## Affiliations [🔬**Shanghai Artificial Intelligence Laboratory** Shanghai · China 2024–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) · [🔬**Shanghai Astronomical Observatory** Shanghai · China 2019–2025 · 4 papersEmployment 2019–2025 · PhD](https://ror.org/003n8re58) · [🏛️**Chinese Academy of Sciences** Beijing · China 2011–2024 · 4 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2021–2024 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) · [🔬**Korea Astronomy and Space Science Institute** Daejeon · South Korea 2025Employment since 2025 · postdoctor](https://ror.org/04g2pxh42) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 11 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Applied Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Materials Science · 1 work](https://md.research.elamur.ai/free/en/shelves/materials-science/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Materials Chemistry · 1 work](https://md.research.elamur.ai/free/en/shelves/materials-science/materials-chemistry/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yuqiang-li/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/yuqiang-li/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2024-llama-berry-pairwise-optimization-o1/)** *(2024 · 49 citations)* LLaMA-Berry is a framework that helps LLMs solve hard math problems, especially at Olympiad level, without retraining the base model. It tackles two weaknesses. Stepwise generation gets little feedback along the way. Iterative self-correction tends to stall in poor local solutions. 2. **[MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses](https://md.research.elamur.ai/free/en/papers/yang-2024-moose-chem-large-language/)** *(2024 · 36 citations)* The paper asks whether LLMs can independently propose new, valid chemistry hypotheses when given only a research background (a question and/or a short survey) from any subfield. 3. **[ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition](https://md.research.elamur.ai/free/en/papers/liu-2025-researchbench-benchmarking-llms-scientific/)** *(2025 · 25 citations)* Scientific hypothesis generation has had no dedicated benchmark for LLMs. ResearchBench addresses this by building on a decomposition from MOOSE-Chem. In that view, a hypothesis comes from combining a research background with one or more inspirations. Discovery can then be split into three sub-tasks: finding… ## Co-authors here 12 of 13 co-authors with a page, the most papers together first. - [Dongzhan Zhou](https://md.research.elamur.ai/free/en/authors/dongzhan-zhou/) ×3 - [Tong Xie](https://md.research.elamur.ai/free/en/authors/tong-xie/) ×3 - [Wanli Ouyang](https://md.research.elamur.ai/free/en/authors/wanli-ouyang/) ×3 - [Ben Gao](https://md.research.elamur.ai/free/en/authors/ben-gao/) ×2 - [Erik Cambria](https://md.research.elamur.ai/free/en/authors/erik-cambria/) ×2 - [Zonglin Yang](https://md.research.elamur.ai/free/en/authors/zonglin-yang/) ×2 - [Di Zhang](https://md.research.elamur.ai/free/en/authors/di-zhang/) - [Jiatong Li](https://md.research.elamur.ai/free/en/authors/jiatong-li/) - [Jinjie Ni](https://md.research.elamur.ai/free/en/authors/jinjie-ni/) - [Shixiang Tang](https://md.research.elamur.ai/free/en/authors/shixiang-tang/) - [Shufei Zhang](https://md.research.elamur.ai/free/en/authors/shufei-zhang/) - [Soujanya Poria](https://md.research.elamur.ai/free/en/authors/soujanya-poria/) ## Cited by Papers of our library cite their works 143 times (of the 149,439 papers whose bibliographies we read); [47 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yuqiang-li/cited-by/). Updated 3 November 2026