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Jackson Petty

Jackson Petty has 4 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Michael Y. Hu, Tal Linzen, William Merrill.

4 papers in our library · 2023–2026

OpenAlex · h-index 5 · 27 works · 84 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 1,073 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #2364

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 States2022–2026 · 12 paperscurrent🤝Center for Applied LinguisticsWashington · United States2026 · 1 papercurrent🎓Yale UniversityNew Haven · United States2021–2022 · 3 papers🏢GoogleMountain View · United States2023–2024 · 2 papers🏢Google DeepMindLondon · United Kingdom2023–2024 · 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.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksInformation Systems · 1 workMathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 2 worksReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Artificial intelligence · 1 work

 Works by year

2020s

20261 paper20251 paper20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. GPQA: A Graduate-Level Google-Proof Q&A Benchmark (2023 · 1,018 citations)
    GPQA addresses a gap in scalable oversight research: testing how people can check AI answers that they cannot verify themselves requires questions that are correct, answerable by real specialists, and still out of reach for capable outsiders who can search the web.
  2. How Abstract Is Linguistic Generalization in Large Language Models? Experiments with Argument Structure (2023 · 29 citations)
    The paper asks whether pre-trained transformer LLMs encode how syntactic contexts relate to one another, beyond knowing which words fit a single context.
  3. Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases (2025 · 9 citations)
    Transformer language models need far more data than humans. This paper asks which properties of a formal language make it a useful warm-up before natural-language training, a setup the authors call pre-pretraining. They propose two criteria, drawing on the Chomsky hierarchy and on circuit complexity. First, the…
  4. RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context (2026)
    LLMs increasingly have to solve tasks by retrieving and combining many pieces of information from their context.

All works

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

  1. GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
  2. (QA)²: Question Answering with Questionable Assumptions ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetNajoung Kim et al.2023 · 39 citations
  3. How Abstract Is Linguistic Generalization in Large Language Models? Experiments with Argument StructureTransactions of the Association for Computational Linguistics (TACL)Michael Wilson, Jackson Petty, Robert Frank2023 · 29 citations
  4. Debate Helps Supervise Unreliable Experts ↗arXiv (Cornell University) · no summary yetJulian Michael et al.2023 · 28 citations
  5. Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic BiasesAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Y. Hu, Jackson Petty, Chuan Shi, et al.2025 · 9 citations
  6. Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction ↗arXiv:2604.07320 · no summary yetJackson Petty, Jaulie Goe, Tal Linzen2026 · 1 citation
  7. RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-ContextTransactions of the Association for Computational Linguistics (TACL)Jackson Petty, Michael Y. Hu, Wentao Wang, et al.2026

 Co-authors here

11 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 1,073 times (of the 149,439 papers whose bibliographies we read); 303 citing papers with a page here →.

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