Elamur Research⌕
☰
home / authors / Marianna Nezhurina

Marianna Nezhurina

Marianna Nezhurina has 2 papers in our library, in 2024–2025, most of them on Language models & pretraining, Reasoning; often with Georgios Smyrnis, Jean Mercat, Sedrick Keh.

2 papers in our library · 2024–2025

OpenAlex · h-index 6 · 24 works · 1,071 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,684 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6844

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

🤝Open SocietyPrague · Czechia2026 · 1 papercurrent

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.

 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workMathematics · 1 work

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

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. OpenThoughts: Data Recipes for Reasoning Models (2025 · 122 citations)
    The strongest reasoning models are usually distilled from training data that is not public, so researchers know little about which data choices actually matter.
  2. Language models scale reliably with over-training and on downstream tasks (2024 · 46 citations)
    Scaling laws let teams forecast large language model behaviour from cheap small runs. Most published laws, however, assume Chinchilla-style compute-optimal training and predict only next-token loss. In practice, smaller models are often over-trained on far more tokens to cut inference cost, and they are compared on…

All works

4 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. BLOOM: A 176B-Parameter Open-Access Multilingual Language Model ↗arXiv:2211.05100 · no summary yetBigScience Workshop et al.2022 · 1,606 citations
  2. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
  3. Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models ↗arXiv:2406.02061 · no summary yetMarianna Nezhurina et al.2024 · 48 citations
  4. Language models scale reliably with over-training and on downstream tasksarXiv:2403.08540Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.2024 · 46 citations

 Co-authors here

12 of 16 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 1,684 times (of the 149,439 papers whose bibliographies we read); 409 citing papers with a page here →.

Updated

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