--- title: "Qizhi Pei — author profile and papers — Elamur Research" description: "Qizhi Pei, Shanghai Artificial Intelligence Laboratory: 5 papers on Elamur Research (2025–2026), h-index 1 — affiliations, topics, co-authors…" canonical: "https://research.elamur.ai/free/en/authors/qizhi-pei/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/qizhi-pei/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Qizhi Pei # Qizhi Pei Qizhi Pei has 5 papers in our library, in 2025–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Lijun Wu](https://md.research.elamur.ai/free/en/authors/lijun-wu/), [Conghui He](https://md.research.elamur.ai/free/en/authors/conghui-he/), [Yu Li](https://md.research.elamur.ai/free/en/authors/yu-li/). 5 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5139829912) · [**h-index 1**](https://openalex.org/authors/A5139829912) · [7 works](https://openalex.org/works?filter=author.id:A5139829912) · [2 citations](https://openalex.org/works?filter=author.id:A5139829912&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/qizhi-pei/#papers) · [🔗 Cited 16 times in our library](https://md.research.elamur.ai/free/en/authors/qizhi-pei/cited-by/) · [⭐ Paper Stars ranking: #10390](https://md.research.elamur.ai/free/en/paper-stars/page/104/#star-10390) 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=Qizhi+Pei) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Qizhi+Pei) · [dblp](https://dblp.org/search?q=Qizhi+Pei) · [ACL Anthology](https://aclanthology.org/search/?q=Qizhi+Pei) ## Affiliations [🔬**Shanghai Artificial Intelligence Laboratory** Shanghai · China 2025–2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) · [🎓**Renmin University of China** Beijing · China 2025–2026 · 5 papers*current*](https://md.research.elamur.ai/free/en/universities/renmin-university-of-china/) 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 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 5 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/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Computational Theory and Mathematics · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Applied Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 4 works](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 [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/qizhi-pei/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/qizhi-pei/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion](https://md.research.elamur.ai/free/en/papers/pei-2025-mathfusion-enhancing-mathematical-problem-solving/)** *(2025 · 10 citations)* Most data augmentation for mathematical SFT changes one problem at a time, for example by rewording it or adjusting its difficulty. 2. **[ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch](https://md.research.elamur.ai/free/en/papers/liu-2026-chartverse-scaling-chart-reasoning-reliable/)** *(2026 · 5 citations)* Open-source vision-language models lag on chart reasoning, mainly because training data is weak. Synthetic charts tend to be simple and repetitive, and automatically generated QA pairs often contain hallucinated or numerically wrong answers. ChartVerse is a code-driven pipeline that builds both charts and reasoning… 3. **[REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once](https://md.research.elamur.ai/free/en/papers/pan-2026-rest-stress-testing-large-reasoning/)** *(2026 · 3 citations)* Standard reasoning benchmarks pose one question per prompt. Many, such as GSM8K and MATH500, are now close to saturated for large reasoning models (LRMs), which forces repeated, costly creation of new test sets. The single-question format also ignores real deployments where a model must handle several queries in one… 4. **[Data Pollination: An Emergent Ecological Process Driving AI Population Evolution](https://md.research.elamur.ai/free/en/papers/xie-2026-data-pollination-emergent-ecological-process/)** *(2026)* The paper argues that language models do not evolve in isolation. Their generated text is published online, scraped into web corpora, and used to train later models, often from other organizations. The authors call this unplanned feedback loop "data pollination" and ask how it affects the risk of model collapse under… 5. **[R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-r-3-end-end-reasoning/)** *(2026)* Multi-step retrosynthesis means breaking a target molecule down, step by step, into purchasable building blocks. ## Co-authors here 12 of 18 co-authors with a page, the most papers together first. - [Lijun Wu](https://md.research.elamur.ai/free/en/authors/lijun-wu/) ×4 - [Conghui He](https://md.research.elamur.ai/free/en/authors/conghui-he/) ×3 - [Yu Li](https://md.research.elamur.ai/free/en/authors/yu-li/) ×3 - [Zhuoshi Pan](https://md.research.elamur.ai/free/en/authors/zhuoshi-pan/) ×3 - [Honglin Lin](https://md.research.elamur.ai/free/en/authors/honglin-lin/) ×2 - [Rui Yan](https://md.research.elamur.ai/free/en/authors/rui-yan/) ×2 - [Xin Gao](https://md.research.elamur.ai/free/en/authors/xin-gao/) ×2 - [Ang Lv](https://md.research.elamur.ai/free/en/authors/ang-lv/) - [H. Vicky Zhao](https://md.research.elamur.ai/free/en/authors/h-vicky-zhao/) - [Hao Zhou](https://md.research.elamur.ai/free/en/authors/hao-zhou/) - [Jiangtao Feng](https://md.research.elamur.ai/free/en/authors/jiangtao-feng/) - [Lei Bai](https://md.research.elamur.ai/free/en/authors/lei-bai/) ## 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/) ×5: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×4, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ## Cited by Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); [6 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/qizhi-pei/cited-by/). Updated 2 November 2026