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Prajjwal Bhargava

Prajjwal Bhargava has 2 papers in our library, in 2021–2023, most of them on Language models & pretraining, Reasoning; often with Aleksandr Drozd, Anna Rogers, Barlas Oguz.

2 papers in our library · 2021–2023

OpenAlex · ORCID · h-index 5 · 20 works · 2,764 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 208 times in our library · ⭐ Paper Stars ranking: #4168

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

🏢MetaLondon · United Kingdom2025 · 1 papercurrent🎓University of OxfordOxford · United Kingdom2025 · 1 papercurrent🎓The University of Texas at DallasRichardson · United States2021–2022 · 5 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.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 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 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20231 paperEffective Long-Context Scaling of Foundation Models20211 paperGeneralization in NLI: Ways (Not) To Go Beyond Simple Heuristics

 Papers

The most cited first (OpenAlex and our library).

  1. Effective Long-Context Scaling of Foundation Models (2023 · 177 citations)
    In 2023, strong long-input handling was mostly available through proprietary APIs. Earlier open attempts to extend context were usually judged only by perplexity or synthetic probes, and they often lost quality on short tasks. This Meta paper introduces Llama 2 Long, a family of 7B–70B models built by continuing to…
  2. Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics (2021 · 127 citations)
    The paper asks whether BERT-style models fine-tuned on MNLI can avoid the shallow cues that the adversarial HANS set is built to expose.

 Co-authors here

10 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 208 times (of the 141,840 papers whose bibliographies we read); 35 citing papers with a page here →.

Updated

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