🧑‍🔬 Yanan Zheng

🏛️ Affiliations

🎓Huazhong University of Science and TechnologyWuhan · China2011–2026 · 4 paperscurrent🏥Central Hospital of WuhanWuhan · China2026 · 1 papercurrent🏢Gilead SciencesFoster City · United States2026 · 1 papercurrent🏥Ruijin HospitalShanghai · China2011–2025 · 30 papers🎓Shanghai Jiao Tong UniversityShanghai · China2011–2025 · 30 papers🏢GenentechSan Francisco2010–2015 · 16 papers🎓Shenyang Agricultural UniversityShenyang · China1999–2023 · 12 papersEducation 1999–2003 · Bachelor, College of Plant ProtectionEducation 2003–2006 · Master, College of Plant ProtectionEducation 2006–2009 · Doctor, College of Plant ProtectionEmployment since 2009 · teacher and researcher, College of Forestry🎓Gannan Medical UniversityGanzhou · China2016–2025 · 10 papers🎓Tsinghua UniversityBeijing · China2017–2023 · 10 papers🏛️National Development and Reform CommissionBeijing · China2016–2020 · 9 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 60 more institutions on single bylines are not listed.

🧭 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. GPT Understands, Too (2021 · 1,054 citations)
   The paper tackles the fragility of hand-written prompts for pretrained language models. In the authors' preliminary tests, small edits to a cloze pattern, sometimes one word, caused large swings in accuracy. Their method, P-Tuning, adds a few trainable continuous vectors to the usual discrete prompt tokens. These…
2. Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models (2026 · 10 citations)
   Process Reward Models (PRMs) score each step of an LLM's mathematical reasoning. They have two weaknesses: they can be gamed through reward hacking, and they need costly step-level annotation. They also penalize a wrong step even when a later step fixes it.

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. GPT Understands, TooAI OpenXiao Liu, Yanan Zheng, Zhengxiao Du, et al.2021 · 1,054 citations
2. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetJing Zhou et al.2022 · 110 citations
3. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYanan Zheng et al.2022 · 34 citations
4. NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework ↗arXiv (Cornell University) · no summary yetXingcheng Yao et al.2021 · 34 citations
5. Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsTeng Wang, Jiang Zhangyi, Zhenqi He, et al.2026 · 10 citations

🤝 Co-authors here

9 co-authors with a page, the most papers together first.

• Jie Tang
• Ming Ding
• Shengjie Ma
• Teng Wang
• Xiao Liu
• Yujie Qian
• Zeyu Li
• Zhengxiao Du
• Zhilin Yang

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• AI Open ×2: AI Open 2021
• Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ×2
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 583 times (of the 149,439 papers whose bibliographies we read); 84 citing papers with a page here →.

Updated 1 November 2026

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