Elamur Research⌕
☰
home / authors / Somshubra Majumdar

Somshubra Majumdar

Somshubra Majumdar has 2 papers in our library, in 2025–2026, most of them on Reasoning, Efficient models & compression; often with Aleksander Ficek, Boris Ginsburg, Sean Narenthiran.

2 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 15 · 62 works · 3,702 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 311 times in our library · ⭐ Paper Stars ranking: #8321

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

🏢NvidiaSanta Clara · United States2020–2026 · 13 paperscurrent🎓University of Illinois ChicagoChicago · United States2017–2021 · 8 papersEducation 2017–2018 · Masters in Computer Science, Computer Science🏢NvidiaReading · United Kingdom2020–2024 · 3 papers🎓University of MumbaiMumbai · India2016 · 3 papers🎓University of Illinois SystemUrbana · United States2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Science Applications · 1 workInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. OpenCodeReasoning: Advancing Data Distillation for Competitive Coding (2025 · 33 citations)
    Distilling reasoning from large models into smaller ones has strongly improved coding performance. However, the best recipes usually depend on closed datasets or say little about how the data was curated. NVIDIA researchers address this with OpenCodeReasoning, a large open supervised fine-tuning corpus for…
  2. Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models (2026 · 1 citation)
    OpenAI and Google DeepMind report gold-medal results at olympiad-level programming contests, but they have disclosed little about how they did it. Open-weight models have lagged behind. NVIDIA researchers present GenCluster, a test-time compute pipeline that aims for the same level openly and reproducibly.

 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 311 times (of the 149,439 papers whose bibliographies we read); 68 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/somshubra-majumdar/