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 (ICARCV, 2020)

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 (EMNLP (Demos), 2022)

Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. - Vincent Plassier; Mehdi Makni; Aleksandr Rubashevskii; Eric Moulines; Maxim Panov (ICML, 2023)

Scalable Batch Acquisition for Deep Bayesian Active Learning. - Aleksandr Rubashevskii; Daria Kotova; Maxim Panov (SDM, 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; et al. (CoRR, 2023)

Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification. - Ekaterina Fadeeva; Aleksandr Rubashevskii; Artem Shelmanov; Sergey Petrakov; Haonan Li 002; Hamdy Mubarak; Evgenii Tsymbalov; Gleb Kuzmin; Alexander Panchenko; Timothy Baldwin; Preslav Nakov; Maxim Panov (ACL (Findings), 2024)

Efficient Conformal Prediction under Data Heterogeneity. - Vincent Plassier; Nikita Kotelevskii; Aleksandr Rubashevskii; Fedor Noskov; Maksim Velikanov; Alexander Fishkov; Samuel Horváth; Martin Takác 001; Eric Moulines; Maxim Panov (AISTATS, 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; et al. (EMNLP (Findings), 2024)

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, 2025)