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Denis Shepelev

Denis Shepelev has 2 papers in our library, in 2026, most of them on Reasoning; often with Andrey Kuznetsov, Andrey Moskalenko, Daria Pugacheva.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 4 · 22 works · 91 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #11949

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

🎓National University of Science and TechnologyMoscow · Russia2026 · 2 paperscurrent🔬Institute for Information Transmission ProblemsMoscow · Russia2015–2022 · 7 papersEmployment since 2015🎓Moscow Institute of Physics and TechnologyDolgoprudny · Russia2015–2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Bring the Apple, Not the Sofa: Impact of Irrelevant Context in Embodied AI Commands on VLA Models (2026)
    Vision-Language-Action (VLA) models are usually tested on short, clean instructions. Real users, however, rephrase commands and wrap them in chatter. This paper measures how much such linguistic noise hurts robot policies. The authors built an evaluation protocol with two kinds of perturbation:
  2. SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space (2026)
    The paper examines how reasoning segmentation models react when users phrase the same request differently.

 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.

Updated

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