--- title: "Adrian de Wynter · Microsoft — author profile and papers" description: "Adrian de Wynter, Microsoft: 3 papers on Elamur Research (2023–2026), h-index 6 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/adrian-de-wynter/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/adrian-de-wynter/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Adrian de Wynter # Adrian de Wynter Adrian de Wynter has 3 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Harshita Diddee](https://md.research.elamur.ai/free/en/authors/harshita-diddee/), [Kalika Bali](https://md.research.elamur.ai/free/en/authors/kalika-bali/), [Mohamed Ahmed](https://md.research.elamur.ai/free/en/authors/mohamed-ahmed/). 3 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5031169451) · [ORCID](https://orcid.org/0000-0003-2679-7241) · [**h-index 6**](https://openalex.org/authors/A5031169451) · [38 works](https://openalex.org/works?filter=author.id:A5031169451) · [108 citations](https://openalex.org/works?filter=author.id:A5031169451&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/adrian-de-wynter/#papers) · [🔗 Cited 102 times in our library](https://md.research.elamur.ai/free/en/authors/adrian-de-wynter/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #8508](https://md.research.elamur.ai/free/en/paper-stars/page/86/#star-8508) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Adrian+de+Wynter) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Adrian+de+Wynter) · [dblp](https://dblp.org/search?q=Adrian+de+Wynter) · [ACL Anthology](https://aclanthology.org/search/?q=Adrian+de+Wynter) ## Affiliations [🏢**Microsoft** Redmond · United States 2023–2026 · 17 papersEmployment · Principal Applied Scientist*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**University of York** York · United Kingdom 2023–2026 · 13 papersEmployment*current*](https://md.research.elamur.ai/free/en/universities/university-of-york/) · [🏢**Microsoft Research** Cambridge · United Kingdom 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/microsoft-research-united-kingdom/) · [🏢**Amazon** Seattle · United States 2019–2020 · 5 papers](https://md.research.elamur.ai/free/en/companies/amazon/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) 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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Philosophy · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/philosophy/) 🧭 Topics 5 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Multilingual & cross-lingual NLP · 1 work](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [English · 1 work](https://md.research.elamur.ai/free/en/topics/english/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/adrian-de-wynter/year/2026/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/adrian-de-wynter/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?](https://md.research.elamur.ai/free/en/papers/hada-2023-large-language-model-based-evaluators/)** *(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](https://md.research.elamur.ai/free/en/papers/li-2026-hrunting-ai-where-improve-english/)** *(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](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/)** *(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:2309.07462**Rishav Hada, Varun Gumma, Adrian de Wynter, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/hada-2023-large-language-model-based-evaluators/) 2. **[LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models ↗](https://arxiv.org/abs/2404.01230) arXiv:2404.01230 · no summary yet**Yadong Zhang et al.*2024 · 44 citations* 3. [**The Hrunting of AI: Where and How to Improve English Dialectal Fairness arXiv:2603.15187**Wei Li, Adrian de Wynter*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/li-2026-hrunting-ai-where-improve-english/) 4. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation* 5. **[A User-Centered Evaluation of Spanish Text Simplification ↗](https://arxiv.org/abs/2308.07556) arXiv:2308.07556 · no summary yet**Adrian de Wynter, Anthony Hevia, Si-Qing Chen*2023* ## Co-authors here 8 co-authors with a page, the most papers together first. - [Harshita Diddee](https://md.research.elamur.ai/free/en/authors/harshita-diddee/) - [Kalika Bali](https://md.research.elamur.ai/free/en/authors/kalika-bali/) - [Mohamed Ahmed](https://md.research.elamur.ai/free/en/authors/mohamed-ahmed/) - [Monojit Choudhury](https://md.research.elamur.ai/free/en/authors/monojit-choudhury/) - [Rishav Hada](https://md.research.elamur.ai/free/en/authors/rishav-hada/) - [Sunayana Sitaram](https://md.research.elamur.ai/free/en/authors/sunayana-sitaram/) - [Varun Gumma](https://md.research.elamur.ai/free/en/authors/varun-gumma/) - [Wei Li](https://md.research.elamur.ai/free/en/authors/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](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/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 →](https://md.research.elamur.ai/free/en/authors/adrian-de-wynter/cited-by/). Updated 31 October 2026