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Xinpeng Wang

Xinpeng Wang has 3 papers in our library, in 2024–2025, most of them on Language models & pretraining, Reasoning; often with Barbara Plank, Bolei Ma, Frauke Kreuter.

3 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 10 · 50 works · 358 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 100 times in our library · ⭐ Paper Stars ranking: #6566

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

🏛️Chinese People's Liberation ArmyBeijing · China2021–2026 · 2 paperscurrent🎓University of MichiganAnn Arbor · United States2017–2023 · 15 papers🎓Wuhan University of TechnologyWuhan · China2022–2025 · 2 papers🎓Ludwig-Maximilians-Universität MünchenMunich · Germany2024 · 2 papers🎓Waseda UniversityTokyo · Japan2021–2024 · 2 papers🎓Guangdong University of TechnologyGuangzhou · China2020–2021 · 2 papers🏢Semiconductor Manufacturing InternationalShanghai · China2010–2013 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 14 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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 work

 Works by year

2020s

20251 paper20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models (2024 · 91 citations)
    Multiple-choice benchmarks often score instruction-tuned LLMs by checking which option letter receives the highest log probability as the first generated token.
  2. “Seeing the Big through the Small”: Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations? (2024 · 18 citations)
    When several annotators disagree on an NLI item for legitimate reasons, the spread of their labels is informative, and researchers capture it as a human judgment distribution (HJD).
  3. Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study (2025 · 10 citations)
    The paper tests whether LLMs show "algorithmic fidelity", meaning whether they can mimic how specific German population groups answer an open-ended survey question.

 Co-authors here

12 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 100 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

Updated

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