Gleb Kuzmin

According to our database, Gleb Kuzmin authored at least 13 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts.

Danil Sivtsov, Ivan Rodkin, Gleb Kuzmin, Yuri Kuratov, Ivan V. Oseledets

CoRR, June, 2025

Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs.

Artem Vazhentsev, Lyudmila Rvanova, Gleb Kuzmin, Ekaterina Fadeeva, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Mrinmaya Sachan, Preslav Nakov, Artem Shelmanov

CoRR, May, 2025

Uncertainty-aware abstention in medical diagnosis based on medical texts.

Artem Vazhentsev, Ivan Sviridov, Alvard Barseghyan, Gleb Kuzmin, Alexander Panchenko, Aleksandr Nesterov, Artem Shelmanov, Maxim Panov

CoRR, February, 2025

Inference-Time Selective Debiasing to Enhance Fairness in Text Classification Models.

Gleb Kuzmin, Neemesh Yadav, Ivan V. Smirnov, Timothy Baldwin, Artem Shelmanov

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

2024

Mental Disorders Detection in the Era of Large Language Models.

Gleb Kuzmin, Petr Strepetov, Maksim Stankevich, Artem Shelmanov, Ivan V. Smirnov

CoRR, 2024

Inference-Time Selective Debiasing.

Gleb Kuzmin, Nemeesh Yadav, Ivan V. Smirnov, Timothy Baldwin, Artem Shelmanov

CoRR, 2024

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

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Uncertainty Estimation for Debiased Models: Does Fairness Hurt Reliability?

Gleb Kuzmin, Artem Vazhentsev, Artem Shelmanov, Xudong Han, Simon Suster, Maxim Panov, Alexander Panchenko, Timothy Baldwin

Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

Hybrid Uncertainty Quantification for Selective Text Classification in Ambiguous Tasks.

Artem Vazhentsev, Gleb Kuzmin, Akim Tsvigun, Alexander Panchenko, Maxim Panov, Mikhail Burtsev, Artem Shelmanov

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Towards Computationally Feasible Deep Active Learning.

Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin, Leonid Sanochkin, Daniil Larionov, Gleb Gusev, Manvel Avetisian, Leonid Zhukov

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

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

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Uncertainty Estimation of Transformer Predictions for Misclassification Detection.

Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, Manvel Avetisian, Leonid Zhukov

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2017

Multidimensional assessment of R&D performance: evidence from the pilot evaluation exercise of Russian public research institutions.

Konstantin Fursov, Gleb Kuzmin

Proceedings of the 16th International Conference on Scientometrics and Informetrics, 2017