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Wenxuan Ding

Wenxuan Ding has 3 papers in our library, in 2026, most of them on Language models & pretraining; often with Shangbin Feng, Alisa Liu, Chen-Yu Lee.

3 papers in our library · 2026

OpenAlex · h-index 4 · 22 works · 88 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 17 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9275

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

🎓New York UniversityNew York · United States2025–2026 · 4 paperscurrent🎓Hong Kong University of Science and TechnologyHong Kong · China2023–2025 · 11 papers🎓The University of Texas at AustinAustin · United States2024–2025 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksSocial Sciences · 1 workComputer Vision and Pattern Recognition · 1 workSociology and Political Science · 1 work

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

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. When One LLM Drools, Multi-LLM Collaboration Rules (2026 · 14 citations)
    This position paper by Feng et al. (ACL 2026) argues that a single general-purpose LLM cannot reliably handle complex, context-dependent, or subjective settings. It contributes no new dataset or model. Instead, it makes a conceptual case that any one model leaves gaps on three fronts. It misses parts of real-world…
  2. Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs (2026 · 2 citations)
    The paper asks how vision-language models handle a conflict between what an image shows and what accompanying text claims.
  3. Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems (2026 · 1 citation)
    Multi-LLM systems increasingly combine models built by different parties, which raises the question of how a compromised participant affects the whole.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. When One LLM Drools, Multi-LLM Collaboration RulesAnnual Meeting of the Association for Computational Linguistics (ACL)Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.2026 · 14 citations
  2. MoCo: A One-Stop Shop for Model Collaboration Research ↗arXiv (Cornell University) · no summary yetShangbin Feng et al.2026 · 3 citations
  3. Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Chi Zhang, Wenxuan Ding, Jiale Liu, et al.2026 · 2 citations
  4. Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.2026 · 1 citation

 Co-authors here

12 of 16 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 17 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/wenxuan-ding/