Aleksandr Rubashevskii

14 papers A* 1A 2C 1Journal 7Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search. CoRR Ekaterina Fadeeva, Maiya Goloburda, Aleksandr Rubashevskii, Roman Vashurin, Artem Shelmanov, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
2025	J	`jnl`	Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation. CoRR Ekaterina Fadeeva, Aleksandr Rubashevskii, Roman Vashurin, Shehzaad Dhuliawala, Artem Shelmanov, Timothy Baldwin, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
2024	A	`conf`	Efficient Conformal Prediction under Data Heterogeneity. AISTATS Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2024	—	`conf`	Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. ACL (Findings) Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
2024	J	`jnl`	Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. CoRR Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
2024	—	`conf`	Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers. EMNLP (Findings) 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
2023	A*	`conf`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Efficient Conformal Prediction under Data Heterogeneity. CoRR Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2023	J	`jnl`	Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output. CoRR 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
2023	A	`conf`	Scalable Batch Acquisition for Deep Bayesian Active Learning. SDM Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
2023	J	`jnl`	Scalable Batch Acquisition for Deep Bayesian Active Learning. CoRR Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
2022	—	`conf`	ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts. EMNLP (Demos) Akim Tsvigun, Leonid Sanochkin, Daniil Larionov, Gleb Kuzmin, Artem Vazhentsev, Ivan Lazichny, Nikita Khromov, Danil Kireev, Aleksandr Rubashevskii, Olga Shahmatova
2020	C	`conf`	Near-Infrared-to-Visible Vein Imaging via Convolutional Neural Networks and Reinforcement Learning. ICARCV Vito M. Leli, Aleksandr Rubashevskii, Aleksandr Sarachakov, Oleg Rogov, Dmitry V. Dylov