Elamur Research⌕
☰
home / authors / Vibhav Vineet

Vibhav Vineet

Vibhav Vineet has 2 papers in our library, in 2024–2025, most of them on Language models & pretraining, Reasoning; often with Akshay Nambi, Eduardo Salinas, Hamid Palangi.

2 papers in our library · 2024–2025

OpenAlex · h-index 27 · 108 works · 8,835 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 86 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #11543

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

🏢MicrosoftRedmond · United States2019–2026 · 52 paperscurrent🎓Oxford Brookes UniversityOxford · United Kingdom2011–2015 · 12 papers🎓University of OxfordOxford · United Kingdom2015 · 6 papers🎓Stanford UniversityStanford · United States2015–2023 · 5 papers🏢IntelSanta Clara · United States2016 · 4 papers🎓International Institute of Information Technology, HyderabadHyderabad · India2008–2010 · 3 papers🏢Microsoft ResearchCambridge · United Kingdom2022 · 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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksApplied Mathematics · 1 workMathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning (2025 · 8 citations)
    Most benchmarks for math word problems (MWPs) check only whether an LLM reaches the right final answer. They largely ignore whether the model can spot and repair flawed reasoning, which matters for tutoring and other educational uses. The authors built MWP-MISTAKE, a benchmark that pairs each problem with correct and…
  2. Eureka: Evaluating and Understanding Large Foundation Models (2024 · 7 citations)
    Evaluating today's large foundation models has become unreliable. Many popular benchmarks are nearly maxed out, measurement setups are rarely disclosed, scoring generative outputs takes complex processing, and leaderboard numbers say little about how models fail. Microsoft Research addresses this with EUREKA, an…

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. Struck: Structured Output Tracking with Kernels ↗IEEE Transactions on Pattern Analysis and Machine Intelligence · no summary yetSam Hare et al.2015 · 998 citations
  2. Dense Monocular Depth Estimation in Complex Dynamic Scenes ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRené Ranftl et al.2016 · 182 citations
  3. Feature Space Optimization for Semantic Video Segmentation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetAbhijit Kundu, Vibhav Vineet, Vladlen Koltun2016 · 180 citations
  4. Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Joykirat Singh, Akshay Nambi, Vibhav Vineet2025 · 8 citations
  5. Eureka: Evaluating and Understanding Large Foundation ModelsarXiv:2409.10566Vidhisha Balachandran, Jingya Chen, Neel Joshi, et al.2024 · 7 citations

 Co-authors here

5 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 86 times (of the 149,439 papers whose bibliographies we read); 24 citing papers with a page here →.

Updated

↑ back to top

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