A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code. - Nadezhda Chirkova; Sergey Troshin 001 (NAACL-HLT, 2021)

Empirical study of transformers for source code. - Nadezhda Chirkova; Sergey Troshin 001 (ESEC/SIGSOFT FSE, 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 001; Daniil Yudakov; Danila Zaev (CoRR, 2021)

Finding Better Precoding in Massive MIMO using Optimization Approach. - Evgeny Bobrov; Dmitry Kropotov; Sergey Troshin 001; Danila Zaev (CoRR, 2021)

Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems. - Evgeny Bobrov; Sergey Troshin 001; Nadezhda Chirkova; Ekaterina Lobacheva; Sviatoslav Panchenko; Dmitry P. Vetrov; Dmitry Kropotov (CoRR, 2021)

Probing Pretrained Models of Source Codes. - Sergey Troshin 001; Nadezhda Chirkova (BlackboxNLP@EMNLP, 2022)

Probing Pretrained Models of Source Code. - Sergey Troshin 001; Nadezhda Chirkova (CoRR, 2022)

CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code. - Nadezhda Chirkova; Sergey Troshin 001 (ICLR, 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; et al. (CoRR, 2023)

Wrapped β-Gaussians with compact support for exact probabilistic modeling on manifolds. - Sergey Troshin 001; Vlad Niculae (Trans. Mach. Learn. Res., 2023)

ARM: Efficient Guided Decoding with Autoregressive Reward Models. - Sergey Troshin 001; Vlad Niculae; Antske Fokkens (CoRR, 2024)

Study on precoding optimization algorithms in massive MIMO system with multi-antenna users. - Evgeny Bobrov; Dmitry Kropotov; Sergey Troshin 001; Danila Zaev (Optim. Methods Softw., 2024)

On the Low-Rank Parametrization of Reward Models for Controlled Language Generation. - Sergey Troshin 001; Vlad Niculae; Antske Fokkens (Trans. Mach. Learn. Res., 2025)