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Nisarg Patel

Nisarg Patel has 2 papers in our library, in 2024, most of them on Language models & pretraining, Reasoning; often with Chitta Baral, Mihir Parmar, Mutsumi Nakamura.

2 papers in our library · 2024

OpenAlex · ORCID · Wikidata · h-index 10 · 96 works · 545 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 97 times in our library · ⭐ Paper Stars ranking: #6415

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 California, San FranciscoSan Francisco · United States2020–2026 · 22 paperscurrent🎓Indrashil UniversityKadi · India2025–2026 · 4 paperscurrent🎓New York UniversityNew York · United States2020–2022 · 20 papers🎓Harvard UniversityCambridge · United States2017–2021 · 15 papers🎓Arizona State UniversityTempe · United States2023–2024 · 7 papers🎓Pandit Deendayal Energy UniversityGandhinagar · India2025 · 2 papers🔬Broad InstituteCambridge · United States2019 · 2 papers🎓Massachusetts Institute of TechnologyCambridge · United States2019 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 works

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models (2024 · 93 citations)
    Most logical reasoning benchmarks for LLMs either blend logic with other skills (LogiQA, ReClor) or stick to one logic type and a few rules such as modus ponens (FOLIO, ProntoQA).
  2. Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models (2024 · 39 citations)
    Benchmarks for logical reasoning in LLMs usually test only single inference steps, rely on a few rules such as modus ponens, or cover only one kind of logic.

 Co-authors here

6 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 97 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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