Aleksandr Rubashevskii

According to our database, Aleksandr Rubashevskii authored at least 12 papers between 2020 and 2026.

Collaborative distances:

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

2026

Adaptive Conformal Prediction for Improving Factuality of Generations by Large Language Models.

Aleksandr Rubashevskii, Dzianis Piatrashyn, Preslav Nakov, Maxim Panov

CoRR, April, 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

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

CoCoA: A Minimum Bayes Risk Framework Bridging Confidence and Consistency for Uncertainty Quantification in LLMs.

Roman Vashurin, Maiya Goloburda, Albina Ilina, Aleksandr Rubashevskii, Preslav Nakov, Artem Shelmanov, Maxim Panov

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers.

Yuxia Wang, Revanth Gangi Reddy, Zain Muhammad Mujahid, Arnav Arora, Aleksandr Rubashevskii, Jiahui Geng, Osama Mohammed Afzal, Liangming Pan, Nadav Borenstein, Aditya Pillai, Isabelle Augenstein, Iryna Gurevych, Preslav Nakov

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

Efficient Conformal Prediction under Data Heterogeneity.

Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output.

Yuxia Wang, Revanth Gangi Reddy, Zain Muhammad Mujahid, Arnav Arora, Aleksandr Rubashevskii, Jiahui Geng, Osama Mohammed Afzal, Liangming Pan, Nadav Borenstein, Aditya Pillai, Isabelle Augenstein, Iryna Gurevych, Preslav Nakov

CoRR, 2023

Scalable Batch Acquisition for Deep Bayesian Active Learning.

Aleksandr Rubashevskii, Daria Kotova, Maxim Panov

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Conformal Prediction for Federated Uncertainty Quantification Under Label Shift.

Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov

Proceedings of the International Conference on Machine Learning, 2023

2022

ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts.

Akim Tsvigun, Leonid Sanochkin, Daniil Larionov, Gleb Kuzmin, Artem Vazhentsev, Ivan Lazichny, Nikita Khromov, Danil Kireev, Aleksandr Rubashevskii, Olga Shahmatova

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2020

Near-Infrared-to-Visible Vein Imaging via Convolutional Neural Networks and Reinforcement Learning.

Vito M. Leli, Aleksandr Rubashevskii, Aleksandr Sarachakov, Oleg Rogov, Dmitry V. Dylov

Proceedings of the 16th International Conference on Control, 2020