🧑‍🔬 Qizhi Pei

🏛️ Affiliations

🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2025–2026 · 6 paperscurrent🎓Renmin University of ChinaBeijing · China2025–2026 · 5 paperscurrent

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion (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 (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 (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. R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning (2026)
   Multi-step retrosynthesis means breaking a target molecule down, step by step, into purchasable building blocks.

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction FusionAnnual Meeting of the Association for Computational Linguistics (ACL)Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.2025 · 10 citations
2. ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from ScratchAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Liu, Honglin Lin, Xiaoyang Wang, et al.2026 · 5 citations
3. REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at OnceAnnual Meeting of the Association for Computational Linguistics (ACL)Zhuoshi Pan, Qizhi Pei, Yu Li, et al.2026 · 3 citations
4. R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)YiFei Wang, Qizhi Pei, Jiangtao Feng, et al.2026
5. Data Pollination: An Emergent Ecological Process Driving AI Population Evolution ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShufang Xie et al.2026

🤝 Co-authors here

12 of 17 co-authors with a page, the most papers together first.

• Conghui He ×3
• Lijun Wu ×3
• Yu Li ×3
• Zhuoshi Pan ×3
• Honglin Lin ×2
• Xin Gao ×2
• H. Vicky Zhao
• Hao Zhou
• Jiangtao Feng
• Lei Bai
• QiYao Sun
• Rui Yan

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) ×5: ACL 2026 ×3, ACL 2025

🔗 Cited by

Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated 1 November 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/qizhi-pei/