---
title: "Artem Vazhentsev — author profile and papers in our library"
description: "Artem Vazhentsev, The University of Melbourne: 4 papers on Elamur Research (2025–2026), h-index 6 — affiliations, topics, co-authors and…"
canonical: "https://research.elamur.ai/free/en/authors/artem-vazhentsev/"
---
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# Artem Vazhentsev

Artem Vazhentsev has 4 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Alexander Panchenko](https://md.research.elamur.ai/free/en/authors/alexander-panchenko/), [Ekaterina Fadeeva](https://md.research.elamur.ai/free/en/authors/ekaterina-fadeeva/), [Timothy Baldwin](https://md.research.elamur.ai/free/en/authors/timothy-baldwin/).

4 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5054388208) · [**h-index 6**](https://openalex.org/authors/A5054388208) · [42 works](https://openalex.org/works?filter=author.id:A5054388208) · [108 citations](https://openalex.org/works?filter=author.id:A5054388208&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/artem-vazhentsev/#papers) · [🔗 Cited 124 times in our library](https://md.research.elamur.ai/free/en/authors/artem-vazhentsev/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6966](https://md.research.elamur.ai/free/en/paper-stars/page/70/#star-6966)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Artem+Vazhentsev) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Artem+Vazhentsev) · [dblp](https://dblp.org/search?q=Artem+Vazhentsev) · [ACL Anthology](https://aclanthology.org/search/?q=Artem+Vazhentsev)

## Affiliations

[🎓**The University of Melbourne** Melbourne · Australia 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/the-university-of-melbourne/) · [🎓**Skolkovo Institute of Science and Technology** Skolkovo · Russia 2022–2025 · 3 papers](https://md.research.elamur.ai/free/en/universities/skolkovo-institute-of-science-and-technology/) · [🤝**AIRI - Artificial Intelligence Research Institute** Moscow · Russia 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/ngos/airi-artificial-intelligence-research-institute/)

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 5 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/artem-vazhentsev/year/2026/) · [**2025** 3 papers](https://md.research.elamur.ai/free/en/authors/artem-vazhentsev/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph](https://md.research.elamur.ai/free/en/papers/vashurin-2025-benchmarking-uncertainty-quantification-methods-large/)** *(2025 · 67 citations)* Uncertainty quantification (UQ) can help flag hallucinated or low-quality outputs of large language models. Earlier work on UQ for LLMs used incompatible methods and evaluation setups, so findings were hard to compare.
2. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/)** *(2025 · 13 citations)* LLMs often produce hallucinated or non-factual output. Many uncertainty quantification (UQ) methods can flag such output, but the strongest ones sample the model repeatedly and are expensive. Density-based scores such as Mahalanobis Distance (MD) are cheap and work well for encoder classifiers, yet earlier…
3. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/)** *(2025 · 10 citations)* LLMs score each new token assuming everything generated so far is correct. If an early token is wrong, the tokens that follow can still look highly confident, so uncertainty estimates built on raw probabilities understate the risk. The authors argue that what matters is a token's unconditional chance of being…
4. **[ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning](https://md.research.elamur.ai/free/en/papers/smirnov-2026-thinkbooster-unified-framework-seamless-test/)** *(2026)* Research on test-time compute (TTC) scaling for LLM reasoning is scattered. Methods are tested under different protocols, model setups and budgets. Most papers report accuracy but not cost, and released code is rarely ready for production. ThinkBooster addresses this with a single open-source framework (MIT license)…

## All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. **[Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph](https://md.research.elamur.ai/free/en/papers/vashurin-2025-benchmarking-uncertainty-quantification-methods-large/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, et al.*2025 · 67 citations*
2. **[LM-Polygraph: Uncertainty Estimation for Language Models ↗](https://arxiv.org/abs/2311.07383) arXiv:2311.07383 · no summary yet**Ekaterina Fadeeva et al.*2023 · 55 citations*
3. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.*2025 · 13 citations*
4. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*
5. **[ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning](https://md.research.elamur.ai/free/en/papers/smirnov-2026-thinkbooster-unified-framework-seamless-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.*2026*

## Co-authors here

12 of 16 co-authors with a page, the most papers together first.

- [Alexander Panchenko](https://md.research.elamur.ai/free/en/authors/alexander-panchenko/) ×3
- [Ekaterina Fadeeva](https://md.research.elamur.ai/free/en/authors/ekaterina-fadeeva/) ×3
- [Timothy Baldwin](https://md.research.elamur.ai/free/en/authors/timothy-baldwin/) ×3
- [Artem Shelmanov](https://md.research.elamur.ai/free/en/authors/artem-shelmanov/) ×2
- [Ivan Lazichny](https://md.research.elamur.ai/free/en/authors/ivan-lazichny/) ×2
- [Lyudmila Rvanova](https://md.research.elamur.ai/free/en/authors/lyudmila-rvanova/) ×2
- [Maxim Panov](https://md.research.elamur.ai/free/en/authors/maxim-panov/) ×2
- [Rui Xing](https://md.research.elamur.ai/free/en/authors/rui-xing/) ×2
- [Abdelrahman Sadallah](https://md.research.elamur.ai/free/en/authors/abdelrahman-sadallah/)
- [Daria Galimzianova](https://md.research.elamur.ai/free/en/authors/daria-galimzianova/)
- [Gleb Kuzmin](https://md.research.elamur.ai/free/en/authors/gleb-kuzmin/)
- [Jingwei Ni](https://md.research.elamur.ai/free/en/authors/jingwei-ni/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)
- [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/)
- [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/): [NAACL 2025](https://md.research.elamur.ai/free/en/venues/naacl/2025/)
- [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/): [Transactions of the Association for Computational Linguistics (TACL) 2025](https://md.research.elamur.ai/free/en/venues/tacl/2025/)

## Cited by

Papers of our library cite their works 124 times (of the 149,439 papers whose bibliographies we read); [31 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/artem-vazhentsev/cited-by/).

Updated 1 November 2026
