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Xiaomeng Ma

Xiaomeng Ma has 2 papers in our library, in 2022–2023, most of them on Morphology, English; often with Lingyu Gao.

2 papers in our library · 2022–2023

OpenAlex · h-index 6 · 16 works · 104 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 15 times in our library · ⭐ Paper Stars ranking: #9161

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

🎓Dongguan University of TechnologyDongguan · China2025–2026 · 2 paperscurrent🎓The Graduate Center, CUNYNew York · United States2022–2023 · 4 papers🏛️Chinese Academy of SciencesBeijing · China2022–2025 · 3 papers🔬Institute of Modern PhysicsLanzhou · China2022–2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksPsychology · 1 workComputer Vision and Pattern Recognition · 1 workDevelopmental and Educational Psychology · 1 work

🧭 Topics 2Research subjects and languages the work is about.English · 1 workMorphology · 1 work

 Works by year

2020s

20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind (2023 · 17 citations)
    Studies disagree on whether large language models have Theory of Mind (ToM). The authors argue that much of this disagreement comes from inconsistent and sometimes invalid testing. Earlier work used a few examples in a single prompt format, or used tasks that tap empathy or social attribution rather than ToM. Drawing…
  2. How do we get there? Evaluating transformer neural networks as cognitive models for English past tense inflection (2022 · 2 citations)
    The paper asks whether a transformer learns the English past tense as symbolic categories (regular or irregular, and a suffix rule) or as pattern association.

 Co-authors here

1 co-author 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 15 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated

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