🧑‍🔬 Yuhan Wu

🏛️ Affiliations

🎓Shenyang University of TechnologyShenyang · China2009–2026 · 64 papersEducation 2009–2013 · BachelorEmployment since 2022 · School of Environmetal and Chemical Engineeringcurrent🎓Shandong UniversityJinan · China2020–2026 · 6 paperscurrent🎓National Taiwan University of Science and TechnologyTaipei · Taiwan2026 · 1 papercurrent🎓Henan Normal UniversityXinxiang · China2019–2024 · 17 papers🎓Nanjing University of Aeronautics and AstronauticsNanjing · China2017–2023 · 15 papers🎓Technische Universität IlmenauIlmenau · Germany2017–2023 · 15 papersEducation 2017–2021 · Ph.D.🎓Soochow UniversitySuzhou · China2020–2024 · 12 papers🎓Nanjing Forestry UniversityNanjing · China2022–2025 · 10 papers🎓Huazhong University of Science and TechnologyWuhan · China2022–2025 · 9 papers🎓Yancheng Institute of TechnologyYancheng · China2023–2025 · 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. RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models (2023 · 187 citations)
   Open-source LLMs are trained for general use and are weak at imitating specific fictional characters. Strong closed models such as GPT-4 can do this, but they are costly, cannot be fine-tuned, and need all character details placed in the prompt. RoleLLM addresses this with a four-stage pipeline. First, the authors…
2. TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation (2025 · 7 citations)
   Compact reasoning models are usually built by fine-tuning a smaller model on a mix of reasoning traces from a much larger teacher.
3. Deputy: Accelerating Large Language Model Inference with Dynamic Low-Rank Substitution (2026 · 1 citation)
   Large language models apply the same dense computation to every token, which wastes resources and slows inference.

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language ModelsarXiv:2310.00746Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.2023 · 187 citations
2. RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models ↗Findings of the Association for Computational Linguistics: ACL 2024 · no summary yetNoah Wang et al.2024 · 114 citations
3. DiaASQ: A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetBobo Li et al.2023 · 70 citations
4. TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge DistillationarXiv:2503.04872Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.2025 · 7 citations
5. Deputy: Accelerating Large Language Model Inference with Dynamic Low-Rank SubstitutionFindings of the Association for Computational LinguisticsYuhua Zhou, Shichao Weng, Changhai Zhou, et al.2026 · 1 citation

🤝 Co-authors here

12 of 19 co-authors with a page, the most papers together first.

• Change Jia
• Changhai Zhou
• Fei Yang
• Guangxiang Zhao
• Haoran Que
• Jiaheng Liu
• Jian Yang
• Jun Gao
• Lin Sun
• Linglin Zhang
• Man Zhang
• Qian Qiao

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: ACL 2023 ×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 209 times (of the 149,439 papers whose bibliographies we read); 39 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/yuhan-wu/