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Vivek Gupta

Vivek Gupta has 2 papers in our library, in 2020–2023, most of them on Language models & pretraining, Reasoning; often with Elena Simperl, Oana Cocarascu, Vivek Srikumar.

2 papers in our library · 2020–2023

OpenAlex · ORCID · h-index 14 · 54 works · 642 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 158 citations in our library · 3 more in our library without a page yet · ⭐ Paper Star rank #4716

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

🎓Arizona State UniversityTempe · United States2024–2026 · 16 paperscurrent🎓University of UtahSalt Lake City · United States2019–2022 · 20 papers🎓Indian Institute of Technology KanpurKanpur · India2016–2022 · 5 papers🎓Indian Institute of Technology GuwahatiGuwahati · India2021–2025 · 4 papers🏢Microsoft ResearchBengaluru · India2016–2020 · 4 papers🏢MicrosoftRedmond · United States2013–2017 · 4 papers🎓Carnegie Mellon UniversityPittsburgh · United States2019–2020 · 3 papers🎓University of PennsylvaniaPhiladelphia · United States2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions 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 5 Arts and Humanities · 2 works Computer Science · 2 works Artificial Intelligence · 2 works Computer Vision and Pattern Recognition · 2 works Language and Linguistics · 2 works

🧭 Topics 2 Language models & pretraining · 1 work Reasoning · 1 work

 Works by year

2020s

20231 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. INFOTABS: Inference on Tables as Semi-structured Data (2020 · 150 citations)
    Gupta et al. ask whether modern NLI systems can reason over semi-structured text rather than ordinary sentences. They introduce INFOTABS, an English inference benchmark whose premises are Wikipedia info-boxes: heterogeneous key-value tables with no fixed schema. Hypotheses are short sentences written by Amazon…
  2. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data (2023 · 38 citations)
    The authors investigate how well language models handle numbers and where exactly they make mistakes. Most previous benchmarks test only isolated aspects of numerical skills. The authors therefore propose a hierarchical taxonomy of eleven types of numerical reasoning. It has four levels, ranging from recognizing how…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. INFOTABS: Inference on Tables as Semi-structured DataVivek Gupta, Maitrey Mehta, Pegah Nokhiz, et al.Annual Meeting of the Association for… · 150 citations
  2. A Logic-Driven Framework for Consistency of Neural Models (original ↗)Tao Li et al.2019 · arXiv:1909.00126 · 59 citations · no summary yet
  3. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataMubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.Findings of the Association for Computational… · 38 citations
  4. Better Call CLAUSE: A Discrepancy Benchmark for Auditing LLMs Legal Reasoning Capabilities (original ↗)Manan Roy Choudhury et al.2026 · Findings of the Association for Computational… · 5 citations · no summary yet
  5. Moneyball with LLMs: Analyzing Tabular Summarization in Sports Narratives (original ↗)Ritam Upadhyay et al.2026 · Findings of the Association for Computational… · no summary yet

 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 158 times (of the 141,840 papers whose bibliographies we read); 9 citing papers with a page here →.

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