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Jenna Russell

Jenna Russell has 3 papers in our library, in 2025–2026; often with Mohit Iyyer, Marzena Karpinska, Chau Minh Pham.

3 papers in our library · 2025–2026

OpenAlex · h-index 2 · 11 works · 24 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 17 times in our library · ⭐ Paper Stars ranking: #8073

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

🎓University of Maryland, College ParkCollege Park · United States2025–2026 · 7 paperscurrent🎓University of Massachusetts AmherstAmherst Center · United States2025–2026 · 3 paperscurrent🏢GoogleMountain View · United States2026 · 2 paperscurrent

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 9The field of science this work belongs to (OpenAlex fields).Social Sciences · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksSociology and Political Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workCommunication · 1 workSafety Research · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text (2025 · 33 citations)
    The paper asks whether people can reliably tell modern LLM output from human prose, given that automatic detectors are often inaccurate, easy to evade and hard to interpret.
  2. AI use in American newspapers is widespread, uneven, and rarely disclosed (2026 · 7 citations)
    Newsrooms are adopting AI tools quickly, but no one has measured how much machine-generated text actually reaches readers of American newspapers.
  3. Frankentext: Stitching random text fragments into long-form narratives (2026 · 1 citation)
    The paper asks whether a black-box LLM user can cheaply produce long stories that read well and still slip past strong AI-text detectors.

 Co-authors here

3 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

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