Ekaterina Fadeeva

According to our database, Ekaterina Fadeeva authored at least 17 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

zDUR: reference-free FASTQ compressor with high compression ratio and speed.

Artem Ershov, Renpeng Ding, Qian Fu, Ivan Kozlov, Ekaterina Fadeeva, Evgeniy Mozheiko, Ming Ni, Yong Hou, Yan Zhou

BMC Bioinform., December, 2026

Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees.

Xueyan Li, Johannes Zenn, Ekaterina Fadeeva, Guinan Su, Mrinmaya Sachan, Jonas Geiping

CoRR, April, 2026

Uncertainty Quantification for Large Language Models.

Maxim Panov, Artem Shelmanov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Lyudmila Rvanova, Timothy Baldwin

Proceedings of the Advances in Information Retrieval, 2026

Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models.

Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, Mubashara Akhtar, Jiaheng Zhang, Elliott Ash, Markus Leippold, Timothy Baldwin, See-Kiong Ng, Artem Shelmanov, Mrinmaya Sachan

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search.

Ekaterina Fadeeva, Maiya Goloburda, Aleksandr Rubashevskii, Roman Vashurin, Artem Shelmanov, Preslav Nakov, Mrinmaya Sachan, Maxim Panov

CoRR, December, 2025

Reasoning with Confidence: Efficient Verification of LLM Reasoning Steps via Uncertainty Heads.

Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, Mubashara Akhtar, Jiaheng Zhang, Elliott Ash, Markus Leippold, Timothy Baldwin, See-Kiong Ng, Artem Shelmanov, Mrinmaya Sachan

CoRR, November, 2025

Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation.

Ekaterina Fadeeva, Aleksandr Rubashevskii, Roman Vashurin, Shehzaad Dhuliawala, Artem Shelmanov, Timothy Baldwin, Preslav Nakov, Mrinmaya Sachan, Maxim Panov

CoRR, May, 2025

Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs.

Artem Vazhentsev, Lyudmila Rvanova, Gleb Kuzmin, Ekaterina Fadeeva, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Mrinmaya Sachan, Preslav Nakov, Artem Shelmanov

CoRR, May, 2025

Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph.

Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, Lyudmila Rvanova, Daniil Vasilev, Akim Tsvigun, Sergey Petrakov, Rui Xing, Abdelrahman Boda Sadallah, Kirill Grishchenkov, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, Artem Shelmanov

Trans. Assoc. Comput. Linguistics, 2025

Data-Driven DSS for Assessing the Viability of Urban and Rural Settlements.

Violetta Gushchina, Danila S. Parygin, Ekaterina Fadeeva, Andrey Alekseev, Artyom Kolyadov

Proceedings of the Novel and Intelligent Digital Systems: Proceedings of the 5th International Conference, 2025

Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models.

Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, Gleb Kuzmin, Ivan Lazichny, Alexander Panchenko, Preslav Nakov, Timothy Baldwin, Maxim Panov, Artem Shelmanov

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs.

Artem Shelmanov, Ekaterina Fadeeva, Akim Tsvigun, Ivan Tsvigun, Zhuohan Xie, Igor Kiselev, Nico Daheim, Caiqi Zhang, Artem Vazhentsev, Mrinmaya Sachan, Preslav Nakov, Timothy Baldwin

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Uncertainty Quantification for Large Language Models.

Artem Shelmanov, Maxim Panov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Timothy Baldwin

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts), 2025

2024

Unconditional Truthfulness: Learning Conditional Dependency for Uncertainty Quantification of Large Language Models.

Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, Alexander Panchenko, Preslav Nakov, Timothy Baldwin, Maxim Panov, Artem Shelmanov

CoRR, 2024

Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph.

Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, Akim Tsvigun, Daniil Vasilev, Rui Xing, Abdelrahman Boda Sadallah, Lyudmila Rvanova, Sergey Petrakov, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, Artem Shelmanov

CoRR, 2024

Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification.

Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

LM-Polygraph: Uncertainty Estimation for Language Models.

Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023