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Vinay Samuel

Vinay Samuel has 2 papers in our library, in 2023–2025, most of them on Language models & pretraining, Question answering, Low-resource languages; often with Aman Chadha, Arijit Ghosh Chowdhury, Henry Peng Zou.

2 papers in our library · 2023–2025

OpenAlex · h-index 4 · 10 works · 37 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 30 times in our library · ⭐ Paper Stars ranking: #8403

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 States2024–2026 · 5 paperscurrent🎓Carnegie Mellon UniversityPittsburgh · United States2024–2025 · 6 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workLow-resource languages · 1 workQuestion answering · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges (2025 · 16 citations)
    Data contamination detectors for LLMs have mostly been validated on older, widely circulated benchmarks and early models such as GPT-J.
  2. Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges (2023 · 16 citations)
    Extractive question answering models perform poorly in specialised domains with few labelled examples, and standard augmentation relies on unlabeled passages such as Wikipedia, which these domains often lack.

 Co-authors here

4 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 30 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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