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Neeraj Varshney

Neeraj Varshney has 3 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Evaluation & benchmarks; often with Chitta Baral, Mihir Parmar, Man Luo.

3 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 22 · 183 works · 1,999 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 797 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6087

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

🎓GLA UniversityMathura · India2019–2026 · 57 paperscurrent🔬National Institute of Standards and TechnologyGaithersburg · United States2018–2026 · 34 papersEmployment since 2018 · Guest Researcher, Wireless Networks Divisioncurrent🏛️Communications Technology LaboratoryGaithersburg · United States2022–2026 · 3 paperscurrent🎓Arizona State UniversityTempe · United States2020–2025 · 38 papers🎓Indian Institute of Technology KanpurKanpur · India2012–2021 · 23 papersEducation 2012–2018 · PhD, Electrical Engineering🎓Punjab Technical UniversityKapurthala Town · India2021–2024 · 5 papers🏢PrometheusSharon · United States2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksReasoning · 3 worksEvaluation & benchmarks · 1 work

 Works by year

2020s

20242 papers20231 paper

 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.
  3. Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models (2023 · 27 citations)
    The paper asks how well language models handle logical reasoning expressed in natural language. Formal knowledge-representation systems needed heavy expert effort and did not scale. The authors first survey the field. They cover three reasoning types (deductive, inductive, abductive), the usual task formats, how…

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetYizhong Wang et al.2022 · 849 citations
  2. NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetSwaroop Mishra et al.2022 · 197 citations
  3. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.2024 · 93 citations
  4. Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Nisarg Patel, Mohith Kulkarni, Mihir Parmar, et al.2024 · 39 citations
  5. Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language ModelsarXiv:2310.00836Man Luo, Shrinidhi Kumbhar, Ming shen, et al.2023 · 27 citations

 Co-authors here

7 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 797 times (of the 149,439 papers whose bibliographies we read); 176 citing papers with a page here →.

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