🧑‍🔬 Ekaterina Fadeeva

🏛️ Affiliations

🎓ETH ZurichZurich · Switzerland2025–2026 · 13 paperscurrent🎓National Research University Higher School of EconomicsMoscow · Russia2023–2025 · 6 papers

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

🧭 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification (2024 · 95 citations)
   LLMs often slip false statements into otherwise accurate text, and readers rarely notice them. The authors propose a fact-checking pipeline that needs no external knowledge base. The output is split into atomic claims (as in FactScore, via the OpenAI Chat API), and each claim is aligned with its tokens. Token-level…
2. Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph (2025 · 66 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.

All works

6 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. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty QuantificationEkaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.Findings of the Association for Computational… · 95 citations
2. Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-PolygraphRoman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, et al.Transactions of the Association for… · 66 citations
3. LM-Polygraph: Uncertainty Estimation for Language Models (original ↗)Ekaterina Fadeeva et al.2023 · arXiv:2311.07383 · 55 citations · no summary yet
4. Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models (original ↗)Artem Vazhentsev et al.2025 · Proceedings of the 2025 Conference on Empirical… · 10 citations · no summary yet
5. ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models (original ↗)Jingwei Ni et al.2026 · Proceedings of the 64th Annual Meeting of the… · 1 citation · no summary yet
6. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning (original ↗)Vladislav Smirnov et al.2026 · Proceedings of the 64th Annual Meeting of the… · no summary yet

🤝 Co-authors here

8 co-authors with a page, the most papers together first.

• Alexander Panchenko ×2
• Sergey Petrakov ×2
• Timothy Baldwin ×2
• Abdelrahman Sadallah
• Artem Shelmanov
• Hamdy Mubarak
• Haonan Li
• Preslav Nakov

Venues

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

• Proceedings of the 64th Annual Meeting of the Association… ×2
• Findings of the Association for Computational Linguistics: 2024
• Transactions of the Association for Computational…: 2025
• Proceedings of the 2025 Conference on Empirical Methods in…

🔗 Cited by

Papers of our library cite their works 179 times (of the 141,840 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated 24 October 2026

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