Aleksandr Rubashevskii

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 11

Top Topics

Active Learning

Imbalanced Data Classification

Conformal Prediction

Top Venues

Publications

Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. CoRR (2024)
Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. ACL (Findings) (2024)
Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
Efficient Conformal Prediction under Data Heterogeneity. AISTATS (2024)
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
Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output. CoRR (2023)
Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR (2023)
Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
Scalable Batch Acquisition for Deep Bayesian Active Learning. SDM (2023)
Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
Efficient Conformal Prediction under Data Heterogeneity. CoRR (2023)
Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML (2023)
Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
Scalable Batch Acquisition for Deep Bayesian Active Learning. CoRR (2023)
Akim Tsvigun, Leonid Sanochkin, Daniil Larionov, Gleb Kuzmin, Artem Vazhentsev, Ivan Lazichny, Nikita Khromov, Danil Kireev, Aleksandr Rubashevskii, Olga Shahmatova
ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts. EMNLP (Demos) (2022)
Vito M. Leli, Aleksandr Rubashevskii, Aleksandr Sarachakov, Oleg Rogov, Dmitry V. Dylov
Near-Infrared-to-Visible Vein Imaging via Convolutional Neural Networks and Reinforcement Learning. ICARCV (2020)