--- title: "John J. Nay — author profile and papers — Elamur Research" description: "John J. Nay: 2 papers on Elamur Research (2023), h-index 15 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/john-j-nay/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/john-j-nay/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / John J. Nay # John J. Nay John J. Nay has 2 papers in our library, in 2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Aran Komatsuzaki](https://md.research.elamur.ai/free/en/authors/aran-komatsuzaki/), [Daniel Paleka](https://md.research.elamur.ai/free/en/authors/daniel-paleka/), [Jungo Kasai](https://md.research.elamur.ai/free/en/authors/jungo-kasai/). 2 papers in our library · 2023 [OpenAlex](https://openalex.org/A5058951556) · [ORCID](https://orcid.org/0000-0002-5961-3528) · [**h-index 15**](https://openalex.org/authors/A5058951556) · [55 works](https://openalex.org/works?filter=author.id:A5058951556) · [792 citations](https://openalex.org/works?filter=author.id:A5058951556&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/john-j-nay/#papers) · [🔗 Cited 109 times in our library](https://md.research.elamur.ai/free/en/authors/john-j-nay/cited-by/) · [4 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #7652](https://md.research.elamur.ai/free/en/paper-stars/page/77/#star-7652) 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=John+J.+Nay) · [Semantic Scholar](https://www.semanticscholar.org/search?q=John+J.+Nay) · [dblp](https://dblp.org/search?q=John+J.+Nay) · [ACL Anthology](https://aclanthology.org/search/?q=John+J.+Nay) ## Affiliations [🎓**New York University** New York · United States 2016–2023 · 18 papers](https://md.research.elamur.ai/free/en/universities/new-york-university/) · [🎓**Stanford University** Stanford · United States 2016–2025 · 15 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Vanderbilt University** Nashville · United States 2014–2018 · 13 papers](https://md.research.elamur.ai/free/en/universities/vanderbilt-university/) · [🎓**Harvard University** Cambridge · United States 2017–2018 · 2 papers](https://md.research.elamur.ai/free/en/universities/harvard-university/) 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 7 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Political Science and International Relations · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/political-science-and-international-relations/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 4 Research subjects and languages the work is about.[Legal AI · 1 work](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/john-j-nay/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[ARB: Advanced Reasoning Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/sawada-2023-arb-advanced-reasoning-benchmark-large/)** *(2023 · 66 citations)* Many popular LLM benchmarks are saturating. Models like GPT-4 now score highly on them even though they still lack expert-level competence. ARB (Advanced Reasoning Benchmark) offers a harder test built from graduate-level and professional problems in mathematics, physics, chemistry, biology and law. The sources were… 2. **[Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence](https://md.research.elamur.ai/free/en/papers/nay-2023-large-language-models-tax-attorneys/)** *(2023 · 49 citations)* The paper asks how well large language models can apply law, using U.S. federal tax law as a testbed. Tax suits this purpose because its authority sits mainly in two fixed sources: the U.S. Code's Title 26 and the Treasury Regulations contained in the CFR. Many tax questions also have one verifiable answer that… ## All works 6 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. [**ARB: Advanced Reasoning Benchmark for Large Language Models arXiv:2307.13692**Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/sawada-2023-arb-advanced-reasoning-benchmark-large/) 2. [**Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence arXiv:2306.07075**John J. Nay, David Karamardian, Sarah B. Lawsky, et al.*2023 · 49 citations*](https://md.research.elamur.ai/free/en/papers/nay-2023-large-language-models-tax-attorneys/) 3. **[Large Language Models as Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards ↗](https://arxiv.org/abs/2301.10095) arXiv:2301.10095 · no summary yet**John J. Nay*2023 · 26 citations* 4. **[Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text ↗](https://aclanthology.org/W16-5607/) Proceedings of the First Workshop on NLP and Computational Social Science · no summary yet**Nay, John J.*2016 · 22 citations* 5. **[Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans ↗](https://arxiv.org/abs/2209.13020) arXiv:2209.13020 · no summary yet**John J. Nay*2022 · 8 citations* 6. **[Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation ↗](https://aclanthology.org/2025.acl-long.1600/) Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Atharvan Dogra et al.*2025 · 2 citations* ## Co-authors here 4 co-authors with a page, the most papers together first. - [Aran Komatsuzaki](https://md.research.elamur.ai/free/en/authors/aran-komatsuzaki/) - [Daniel Paleka](https://md.research.elamur.ai/free/en/authors/daniel-paleka/) - [Jungo Kasai](https://md.research.elamur.ai/free/en/authors/jungo-kasai/) - [Sarah B. Lawsky](https://md.research.elamur.ai/free/en/authors/sarah-b-lawsky/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) - Proceedings of the First Workshop on NLP and Computational Social Science ## Cited by Papers of our library cite their works 109 times (of the 149,439 papers whose bibliographies we read); [33 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/john-j-nay/cited-by/). Updated 2 November 2026