--- title: "Shuai Wang · Tianjin University — author profile and papers" description: "Shuai Wang, Tianjin University: 8 papers on Elamur Research (2021–2026), h-index 32 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/shuai-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/shuai-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Shuai Wang # Shuai Wang Shuai Wang has 8 papers in our library, in 2021–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Coreference resolution](https://md.research.elamur.ai/free/en/topics/coreference-resolution/); often with [Chengfeng Dou](https://md.research.elamur.ai/free/en/authors/chengfeng-dou/), [Fan Yang](https://md.research.elamur.ai/free/en/authors/fan-yang/), [Fei Li](https://md.research.elamur.ai/free/en/authors/fei-li/). 8 papers in our library · 2021–2026 [OpenAlex](https://openalex.org/A5053892249) · [ORCID](https://orcid.org/0000-0003-3730-6401) · [Wikidata](https://www.wikidata.org/wiki/Q86122155) · [**h-index 32**](https://openalex.org/authors/A5053892249) · [201 works](https://openalex.org/works?filter=author.id:A5053892249) · [3,484 citations](https://openalex.org/works?filter=author.id:A5053892249&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 8 works in our library](https://md.research.elamur.ai/free/en/authors/shuai-wang/#papers) · [🔗 Cited 92 times in our library](https://md.research.elamur.ai/free/en/authors/shuai-wang/cited-by/) · [⭐ Paper Stars ranking: #7302](https://md.research.elamur.ai/free/en/paper-stars/page/74/#star-7302) 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=Shuai+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shuai+Wang) · [dblp](https://dblp.org/search?q=Shuai+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Shuai+Wang) ## Affiliations [🎓**Hangzhou Dianzi University** Hangzhou · China 2014–2026 · 29 papers*current*](https://md.research.elamur.ai/free/en/universities/hangzhou-dianzi-university/) · [🎓**Shaanxi University of Technology** Hanzhong · China 2018–2026 · 2 papers*current*](https://ror.org/056m91h77) · [🎓**Southwest Petroleum University** Chengdu · China 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/southwest-petroleum-university/) · [🎓**Tianjin University** Tianjin · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/tianjin-university/) · [🎓**Shandong University** Jinan · China 2011–2025 · 27 papers](https://md.research.elamur.ai/free/en/universities/shandong-university/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2011–2025 · 23 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🎓**Shandong Academy of Sciences** Jinan · China 2011–2023 · 15 papers](https://md.research.elamur.ai/free/en/universities/shandong-academy-of-sciences/) · [🎓**University of North Carolina at Chapel Hill** Chapel Hill · United States 2018–2021 · 15 papers](https://md.research.elamur.ai/free/en/universities/university-of-north-carolina-at-chapel-hill/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2014–2025 · 12 papers](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) · [🔬**State Key Laboratory of Robotics** Liaoning 2014–2020 · 10 papers](https://ror.org/03pcw1780) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 68 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. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Medicine · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Health Informatics · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Statistics, Probability and Uncertainty · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/statistics-probability-and-uncertainty/) 🧭 Topics 2 Research subjects and languages the work is about.[Coreference resolution · 1 work](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/shuai-wang/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/shuai-wang/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/shuai-wang/year/2024/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/authors/shuai-wang/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/)** *(2025 · 40 citations)* Large language models react unpredictably to small changes in prompt wording, ordering or formatting. Manual prompt engineering is therefore laborious and quickly becomes outdated as models change. This survey by an Amazon Web Services team reviews black-box Automatic Prompt Optimization (APO): methods that improve… 2. **[Symbolic Learning Enables Self-Evolving Agents](https://md.research.elamur.ai/free/en/papers/zhou-2024-symbolic-learning-enables-self-evolving/)** *(2024 · 34 citations)* Building LLM-based agents today depends mostly on hand engineering. Developers split a task into steps, then write prompts and attach tools for each step. Earlier automatic optimizers such as DSPy, GPTSwarm, Agent-pro and AgentOptimizer tune only isolated parts, so they can get stuck in local optima. The authors… 3. **[Sequential Cross-Document Coreference Resolution](https://md.research.elamur.ai/free/en/papers/allaway-2021-sequential-cross-document-coreference-resolution/)** *(2021 · 22 citations)* The paper addresses cross-document coreference resolution (CDCR), which groups mentions of the same entity or event across several texts. 4. **[StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2024-steptool-enhancing-multi-step-tool/)** *(2024 · 20 citations)* Large language models still have trouble calling external APIs reliably over several turns. Most earlier work trains them with supervised fine-tuning on expert trajectories. That approach treats tool use as plain text generation and ignores that it is a sequence of decisions. StepTool instead casts tool learning as a… 5. **[Baichuan-M2: Scaling Medical Capability with Large Verifier System](https://md.research.elamur.ai/free/en/papers/team-2025-m2-baichuan-m2-scaling-medical/)** *(2025 · 19 citations)* Medical LLMs often do well on exam-style tests such as USMLE but less well in real consultations, where information comes in gradually over many turns and communication matters. 6. **[Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making](https://md.research.elamur.ai/free/en/papers/team-2026-m3-baichuan-m3-modeling-clinical/)** *(2026 · 2 citations)* Medical LLMs score well on static benchmarks but often stall in real consultations: they rarely ask for missing facts, and they may hallucinate when filling gaps. 7. **[AutoBool: Reinforcement-Learned LLM for Effective Automatic Systematic Reviews Boolean Query Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-autobool-reinforcement-learned-llm-effective/)** *(2026)* Medical systematic reviews depend on Boolean search queries that capture nearly all relevant studies while keeping screening workload manageable. 8. **[When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors](https://md.research.elamur.ai/free/en/papers/yang-2026-when-llms-read-tables-carelessly/)** *(2026)* Even when LLMs parse a table correctly, they often misread it during reasoning. They cite the wrong cell, mix up columns, or skip relevant rows. The authors call these slips data referencing errors (DREs) and split them into two types: Incorrect Citation and Omitted Information. Earlier work looked at DREs only… ## Co-authors here 12 of 39 co-authors with a page, the most papers together first. - [Chengfeng Dou](https://md.research.elamur.ai/free/en/authors/chengfeng-dou/) ×2 - [Fan Yang](https://md.research.elamur.ai/free/en/authors/fan-yang/) ×2 - [Fei Li](https://md.research.elamur.ai/free/en/authors/fei-li/) ×2 - [Jiyuan Jia](https://md.research.elamur.ai/free/en/authors/jiyuan-jia/) ×2 - [Qiang Ju](https://md.research.elamur.ai/free/en/authors/qiang-ju/) ×2 - [Tianpeng Li](https://md.research.elamur.ai/free/en/authors/tianpeng-li/) ×2 - [Xiangrong Zeng](https://md.research.elamur.ai/free/en/authors/xiangrong-zeng/) ×2 - [Yijie Zhou](https://md.research.elamur.ai/free/en/authors/yijie-zhou/) ×2 - [Zhengyuan Shen](https://md.research.elamur.ai/free/en/authors/zhengyuan-shen/) ×2 - [Bevan Koopman](https://md.research.elamur.ai/free/en/authors/bevan-koopman/) - [Boran Han](https://md.research.elamur.ai/free/en/authors/boran-han/) - [Chong Liu](https://md.research.elamur.ai/free/en/authors/chong-liu/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/) ×2: [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/), [EMNLP 2021](https://md.research.elamur.ai/free/en/venues/emnlp/2021/) - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [ACM International Conference on Information and Knowledge Management (CIKM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-information-and-knowledge-management-cikm/): [CIKM 2024](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-information-and-knowledge-management-cikm/2024/) - [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/) ## Cited by Papers of our library cite their works 92 times (of the 149,439 papers whose bibliographies we read); [36 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/shuai-wang/cited-by/). Updated 2 November 2026