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Vijay Kumar Mago

Vijay Kumar Mago has 2 papers in our library, in 2022–2026, most of them on Sentiment & emotion, Vision & language.

2 papers in our library · 2022–2026

OpenAlex · ORCID · Wikidata · h-index 23 · 174 works · 2,576 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4 times in our library · ⭐ Paper Stars ranking: #9101

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

🎓York UniversityToronto · Canada2023–2026 · 31 paperscurrent🎓Lakehead UniversityThunder Bay · Canada2015–2023 · 79 papers🎓Simon Fraser UniversityBurnaby · Canada2010–2013 · 14 papers🎓Troy UniversityTroy · United States2013–2015 · 9 papers🎓DAV UniversityJalandhar · India2005–2011 · 8 papers🔬Mayo ClinicRochester · United States2023 · 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksPsychology · 1 workSocial Psychology · 1 workArts and Humanities · 1 workComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Sentiment & emotion · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. A Survey on Automated Sarcasm Detection on Twitter (2022 · 19 citations)
    Sarcasm usually wears a positive surface over a negative intent. When a sentiment or opinion-mining system takes such a Tweet literally, it gets the polarity wrong. Moores and Mago survey automated sarcasm detection on Twitter and restrict themselves to papers from high-quality venues. They argue that earlier surveys…
  2. Compact Multimodal Language Models as Robust OCR Alternatives for Noisy Textual Clinical Reports (2026 · 1 citation)
    Hospitals often digitize printed medical reports by photographing them with smartphones. The resulting images suffer from blur, shadows, rotation, bleed-through and background clutter, and conventional OCR handles these poorly. This study asks whether small multimodal language models (up to 14B parameters) that can…

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 4 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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