Sergey Troshin

According to our database, Sergey Troshin authored at least 13 papers between 2021 and 2025.

Collaborative distances:

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

2025

On the Low-Rank Parametrization of Reward Models for Controlled Language Generation.

Sergey Troshin, Vlad Niculae, Antske Fokkens

Trans. Mach. Learn. Res., 2025

2024

Study on precoding optimization algorithms in massive MIMO system with multi-antenna users.

Evgeny Bobrov, Dmitry Kropotov, Sergey Troshin, Danila Zaev

Optim. Methods Softw., 2024

ARM: Efficient Guided Decoding with Autoregressive Reward Models.

Sergey Troshin, Vlad Niculae, Antske Fokkens

CoRR, 2024

2023

Wrapped β-Gaussians with compact support for exact probabilistic modeling on manifolds.

Sergey Troshin, Vlad Niculae

Trans. Mach. Learn. Res., 2023

SantaCoder: don't reach for the stars!

Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Muñoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy-Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca, Sourab Mangrulkar, David Lansky, Huu Nguyen, Danish Contractor, Luis Villa, Jia Li, Dzmitry Bahdanau, Yacine Jernite, Sean Hughes, Daniel Fried, Arjun Guha, Harm de Vries, Leandro von Werra

CoRR, 2023

CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code.

Nadezhda Chirkova, Sergey Troshin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Probing Pretrained Models of Source Code.

Sergey Troshin, Nadezhda Chirkova

CoRR, 2022

Probing Pretrained Models of Source Codes.

Sergey Troshin, Nadezhda Chirkova

Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

2021

Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems.

Evgeny Bobrov, Sergey Troshin, Nadezhda Chirkova, Ekaterina Lobacheva, Sviatoslav Panchenko, Dmitry P. Vetrov, Dmitry Kropotov

CoRR, 2021

Finding Better Precoding in Massive MIMO using Optimization Approach.

Evgeny Bobrov, Dmitry Kropotov, Sergey Troshin, Danila Zaev

CoRR, 2021

Adaptive Regularized Zero-Forcing Beamforming in Massive MIMO with Multi-Antenna Users.

Evgeny Bobrov, Boris Chinyaev, Viktor Kuznetsov, Hao Lu, Dmitrii Minenkov, Sergey Troshin, Daniil Yudakov, Danila Zaev

CoRR, 2021

Empirical study of transformers for source code.

Nadezhda Chirkova, Sergey Troshin

Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code.

Nadezhda Chirkova, Sergey Troshin

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021