🧑‍🔬 Adrian de Wynter

🏛️ Affiliations

🏢MicrosoftRedmond · United States2023–2026 · 17 papersEmployment · Principal Applied Scientistcurrent🎓University of YorkYork · United Kingdom2023–2026 · 13 papersEmploymentcurrent🏢Microsoft ResearchCambridge · United Kingdom2026 · 1 papercurrent🏢AmazonSeattle · United States2019–2020 · 5 papers🎓Carnegie Mellon UniversityPittsburgh · United States2023–2024 · 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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation? (2023 · 69 citations)
   Scaling LLM evaluation beyond English is difficult. Benchmarks cover few languages and few realistic tasks, automatic metrics handle rich morphology and unusual scripts poorly, and native-speaker judges are costly and slow. The authors test whether GPT-4, scoring outputs without reference texts, can replace or…
2. The Hrunting of AI: Where and How to Improve English Dialectal Fairness (2026 · 1 citation)
   Large language models handle mainstream English well but perform worse on its dialects, and fixing this is hard when native-speaker data is scarce.
3. The Thin Line Between Comprehension and Persuasion in LLMs (2026 · 1 citation)
   LLMs can sustain fluent, convincing conversations, but does that persuasiveness come with a real grasp of the discussion? The authors test this through informal debates.

All works

5 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. Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?arXiv:2309.07462Rishav Hada, Varun Gumma, Adrian de Wynter, et al.2023 · 69 citations
2. LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models ↗arXiv:2404.01230 · no summary yetYadong Zhang et al.2024 · 44 citations
3. The Hrunting of AI: Where and How to Improve English Dialectal FairnessarXiv:2603.15187Wei Li, Adrian de Wynter2026 · 1 citation
4. The Thin Line Between Comprehension and Persuasion in LLMsFindings of the Association for Computational LinguisticsAdrian de Wynter, Tangming Yuan2026 · 1 citation
5. A User-Centered Evaluation of Spanish Text Simplification ↗arXiv:2308.07556 · no summary yetAdrian de Wynter, Anthony Hevia, Si-Qing Chen2023

🤝 Co-authors here

8 co-authors with a page, the most papers together first.

• Harshita Diddee
• Kalika Bali
• Mohamed Ahmed
• Monojit Choudhury
• Rishav Hada
• Sunayana Sitaram
• Varun Gumma
• Wei Li

Venues

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

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 102 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

Updated 31 October 2026

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