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Shuai Wang

Shuai Wang has 8 papers in our library, in 2021–2026, most of them on Language models & pretraining, Coreference resolution; often with Chengfeng Dou, Fan Yang, Fei Li.

8 papers in our library · 2021–2026

OpenAlex · ORCID · Wikidata · h-index 32 · 201 works · 3,484 citations OpenAlex, 2026-10-14

📄 8 works in our library · 🔗 Cited 92 times in our library · ⭐ Paper Stars ranking: #7302

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Hangzhou Dianzi UniversityHangzhou · China2014–2026 · 29 paperscurrent🎓Shaanxi University of TechnologyHanzhong · China2018–2026 · 2 paperscurrent🎓Southwest Petroleum UniversityChengdu · China2025–2026 · 2 paperscurrent🎓Tianjin UniversityTianjin · China2026 · 1 papercurrent🎓Shandong UniversityJinan · China2011–2025 · 27 papers🏛️Chinese Academy of SciencesBeijing · China2011–2025 · 23 papers🎓Shandong Academy of SciencesJinan · China2011–2023 · 15 papers🎓University of North Carolina at Chapel HillChapel Hill · United States2018–2021 · 15 papers🎓University of Chinese Academy of SciencesBeijing · China2014–2025 · 12 papers🔬State Key Laboratory of RoboticsLiaoning2014–2020 · 10 papers

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 10The field of science this work belongs to (OpenAlex fields).Computer Science · 8 worksArts and Humanities · 6 worksArtificial Intelligence · 8 worksLanguage and Linguistics · 6 worksComputer Vision and Pattern Recognition · 5 worksMedicine · 2 worksInformation Systems · 2 worksHealth Informatics · 2 worksDecision Sciences · 1 workStatistics, Probability and Uncertainty · 1 work

🧭 Topics 2Research subjects and languages the work is about.Coreference resolution · 1 workLanguage models & pretraining · 3 works

 Works by year

2020s

20263 papers20252 papers20242 papers20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. A Systematic Survey of Automatic Prompt Optimization Techniques (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 (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 (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 (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 (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 (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 (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 (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.

Venues

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

 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 →.

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