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Wei Dong

Wei Dong has 2 papers in our library, in 2026, most of them on Reasoning, Language models & pretraining, Efficient models & compression; often with Lan-Zhe Guo, Ming Yang, Yunpeng Li.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 8 · 21 works · 205 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 3 times in our library · ⭐ Paper Stars ranking: #11015

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

🎓Nanyang Technological UniversitySingapore · Singapore2024–2026 · 42 paperscurrent🎓Hong Kong University of Science and TechnologyHong Kong · China2021–2024 · 12 papers🎓Carnegie Mellon UniversityPittsburgh · United States2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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).Computer Science · 2 worksArts and Humanities · 1 workArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksComputational Theory and Mathematics · 1 workLanguage and Linguistics · 1 workHardware and Architecture · 1 work

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksEfficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. TabularMath: Understanding Math Reasoning over Tables with Large Language Models (2026 · 3 citations)
    Most math benchmarks for LLMs use plain-text word problems. Real tasks such as business intelligence or financial reports instead require multi-step arithmetic over tables that may be large, incomplete, or contradictory. Existing table benchmarks rely on manual collection, which limits their scale, and they seldom…
  2. ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks (2026)
    Reasoning-capable LLMs are costly to build. A competitor can still copy their step-by-step behavior by querying a deployed model and training a student on its outputs, including the reasoning traces. Conventional text watermarks (token-level logit biases or sampling rules) tend to disappear in this process, because…

 Co-authors here

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

Updated

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