| Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output Y Wang, RG Reddy, ZM Mujahid, A Arora, A Rubashevskii, J Geng, ... arXiv preprint arXiv:2311.09000, 2023 | 25 | 2023 |
| Near-infrared-to-visible vein imaging via convolutional neural networks and reinforcement learning VM Leli, A Rubashevskii, A Sarachakov, O Rogov, DV Dylov 2020 16th International Conference on Control, Automation, Robotics and …, 2020 | 13 | 2020 |
| Fact-checking the output of large language models via token-level uncertainty quantification E Fadeeva, A Rubashevskii, A Shelmanov, S Petrakov, H Li, H Mubarak, ... arXiv preprint arXiv:2403.04696, 2024 | 10 | 2024 |
| Conformal prediction for federated uncertainty quantification under label shift V Plassier, M Makni, A Rubashevskii, E Moulines, M Panov International Conference on Machine Learning, 27907-27947, 2023 | 9 | 2023 |
| Factcheck-Bench: fine-grained evaluation benchmark for automatic fact-checkers Y Wang, RG Reddy, ZM Mujahid, A Arora, A Rubashevskii, J Geng, ... arXiv preprint arXiv:2311.09000, 2024 | 6 | 2024 |
| ALToolbox: a set of tools for active learning annotation of natural language texts A Tsvigun, L Sanochkin, D Larionov, G Kuzmin, A Vazhentsev, I Lazichny, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 4 | 2022 |
| Scalable batch acquisition for deep bayesian active learning A Rubashevskii, D Kotova, M Panov Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 2 | 2023 |
| Efficient Conformal Prediction under Data Heterogeneity V Plassier, N Kotelevskii, A Rubashevskii, F Noskov, M Velikanov, ... International Conference on Artificial Intelligence and Statistics, 4879-4887, 2024 | 1 | 2024 |
Preslav NakovMBZUAI在 mbzuai.ac.ae 的电子邮件经过验证
