Aleksandr Rubashevskii
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
8
Venues
6
Active years
2020–2026
Best venue rank
A*
Where they publish
Papers
8 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval-Augmented Generation. | Ekaterina Fadeeva, Aleksandr Rubashevskii, Dzianis Piatrashyn, Roman Vashurin, Shehzaad Dhuliawala, Artem Shelmanov, Timothy Baldwin, Preslav Nakov, Mrinmaya Sachan, Maxim Panov |
| 2024 | ACL | 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 |
| 2024 | AISTATS | Efficient Conformal Prediction under Data Heterogeneity. | Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horvth, Martin Takc, Eric Moulines, Maxim Panov |
| 2024 | EMNLP | 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 |
| 2023 | ICML | Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. | Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov |
| 2023 | SDM | Scalable Batch Acquisition for Deep Bayesian Active Learning. | Aleksandr Rubashevskii, Daria Kotova, Maxim Panov |
| 2022 | EMNLP | 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 |
| 2020 | ICARCV | 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 |