--- title: "Zhiwei Fei · Nanjing University — author profile and papers" description: "Zhiwei Fei, Nanjing University: 4 papers on Elamur Research (2023–2026), h-index 1 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/zhiwei-fei/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhiwei-fei/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhiwei Fei # Zhiwei Fei Zhiwei Fei has 4 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Legal AI](https://md.research.elamur.ai/free/en/topics/legal-ai/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/), [Fengzhe Zhou](https://md.research.elamur.ai/free/en/authors/fengzhe-zhou/), [Songyang Zhang](https://md.research.elamur.ai/free/en/authors/songyang-zhang/). 4 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5125679589) · [ORCID](https://orcid.org/0009-0009-3166-8525) · [**h-index 1**](https://openalex.org/authors/A5125679589) · [10 works](https://openalex.org/works?filter=author.id:A5125679589) · [3 citations](https://openalex.org/works?filter=author.id:A5125679589&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/#papers) · [🔗 Cited 230 times in our library](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/cited-by/) · [⭐ Paper Stars ranking: #5803](https://md.research.elamur.ai/free/en/paper-stars/page/59/#star-5803) 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=Zhiwei+Fei) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhiwei+Fei) · [dblp](https://dblp.org/search?q=Zhiwei+Fei) · [ACL Anthology](https://aclanthology.org/search/?q=Zhiwei+Fei) ## Affiliations [🎓**Nanjing University** Nanjing · China 2026 · 6 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 9 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/) · [Social Sciences · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Law · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/law/) · [Political Science and International Relations · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/political-science-and-international-relations/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 3 Research subjects and languages the work is about.[Legal AI · 2 works](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/year/2026/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[LawBench: Benchmarking Legal Knowledge of Large Language Models](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)** *(2023 · 188 citations)* Existing legal benchmarks for LLMs mostly target English-language common-law systems (US, EU) or bar-exam-style questions. 2. **[MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark](https://md.research.elamur.ai/free/en/papers/liu-2024-mathbench-evaluating-theory-application-proficiency/)** *(2024 · 70 citations)* Popular math benchmarks such as GSM8k or MathQA mostly test one narrow skill. They say little about difficulty or about whether a model actually knows the underlying theory. MathBench addresses this with a bilingual (Chinese–English) test set that follows a learning path: an Arithmetic stage, then Primary, Middle… 3. **[InternLM-Law: An Open Source Chinese Legal Large Language Model](https://md.research.elamur.ai/free/en/papers/fei-2024-internlm-law-open-source/)** *(2024 · 9 citations)* General-purpose LLMs often fail on Chinese legal questions, and earlier Chinese legal models were narrow, consultation-oriented, and built on older backbones. 4. **[OpenCompass: A Universal Evaluation Platform for Large Language Models](https://md.research.elamur.ai/free/en/papers/cao-2026-opencompass-universal-evaluation-platform/)** *(2026 · 1 citation)* Judging an LLM's overall quality usually means running dozens or hundreds of static benchmarks. Each benchmark has its own scoring method (regex matching, ROUGE, model-based judging), its own sensitivity to prompts, and its own data preparation and output cleanup. This fragmentation makes large, cross-domain… ## Co-authors here 12 of 18 co-authors with a page, the most papers together first. - [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/) ×4 - [Fengzhe Zhou](https://md.research.elamur.ai/free/en/authors/fengzhe-zhou/) ×3 - [Songyang Zhang](https://md.research.elamur.ai/free/en/authors/songyang-zhang/) ×3 - [Dahua Lin](https://md.research.elamur.ai/free/en/authors/dahua-lin/) ×2 - [Dawei Zhu](https://md.research.elamur.ai/free/en/authors/dawei-zhu/) ×2 - [Haodong Duan](https://md.research.elamur.ai/free/en/authors/haodong-duan/) ×2 - [Hongwei Liu](https://md.research.elamur.ai/free/en/authors/hongwei-liu/) ×2 - [Jidong Ge](https://md.research.elamur.ai/free/en/authors/jidong-ge/) ×2 - [Maosong Cao](https://md.research.elamur.ai/free/en/authors/maosong-cao/) ×2 - [Wenwei Zhang](https://md.research.elamur.ai/free/en/authors/wenwei-zhang/) ×2 - [Xiaoyu Shen](https://md.research.elamur.ai/free/en/authors/xiaoyu-shen/) ×2 - [Chengqi Lyu](https://md.research.elamur.ai/free/en/authors/chengqi-lyu/) ## 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/): [Findings of the Association for Computational Linguistics 2024](https://md.research.elamur.ai/free/en/venues/findings/2024/) ## Cited by Papers of our library cite their works 230 times (of the 149,439 papers whose bibliographies we read); [50 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhiwei-fei/cited-by/). Updated 2 November 2026