Nadezhda Chirkova

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 33

Top Topics

Plagiarism Detection

Knowledge Transfer

Top Venues

Publications

Nadezhda Chirkova, Vassilina Nikoulina
Zero-shot cross-lingual transfer in instruction tuning of large language model. CoRR (2024)
David Rau, Hervé Déjean, Nadezhda Chirkova, Thibault Formal, Shuai Wang, Vassilina Nikoulina, Stéphane Clinchant
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation. CoRR (2024)
Nadezhda Chirkova, Vassilina Nikoulina
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks. CoRR (2024)
Nadezhda Chirkova, Vassilina Nikoulina
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks. NAACL-HLT (2024)
Nadezhda Chirkova, Vassilina Nikoulina, Jean-Luc Meunier, Alexandre Bérard
Investigating the potential of Sparse Mixtures-of-Experts for multi-domain neural machine translation. CoRR (2024)
Nadezhda Chirkova, David Rau, Hervé Déjean, Thibault Formal, Stéphane Clinchant, Vassilina Nikoulina
Retrieval-augmented generation in multilingual settings. CoRR (2024)
Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman
Should you marginalize over possible tokenizations? CoRR (2023)
Nadezhda Chirkova, Sheng Liang, Vassilina Nikoulina
Empirical study of pretrained multilingual language models for zero-shot cross-lingual generation. CoRR (2023)
Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman
Should you marginalize over possible tokenizations? ACL (2) (2023)
Nadezhda Chirkova, Sergey Troshin
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code. ICLR (2023)
Nadezhda Chirkova, Sergey Troshin
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code. CoRR (2023)
Sergey Troshin, Nadezhda Chirkova
Probing Pretrained Models of Source Code. CoRR (2022)
Sergey Troshin, Nadezhda Chirkova
Probing Pretrained Models of Source Codes. BlackboxNLP@EMNLP (2022)
Shamil Ayupov, Nadezhda Chirkova
Parameter-Efficient Finetuning of Transformers for Source Code. CoRR (2022)
Nadezhda Chirkova, Sergey Troshin
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code. NAACL-HLT (2021)
Nadezhda Chirkova, Sergey Troshin
Empirical study of transformers for source code. ESEC/SIGSOFT FSE (2021)
Evgeny Bobrov, Sergey Troshin, Nadezhda Chirkova, Ekaterina Lobacheva, Sviatoslav Panchenko, Dmitry P. Vetrov, Dmitry Kropotov
Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems. CoRR (2021)
Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. NeurIPS (2021)
Ildus Sadrtdinov, Nadezhda Chirkova, Ekaterina Lobacheva
On the Memorization Properties of Contrastive Learning. CoRR (2021)
Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. CoRR (2021)
Nadezhda Chirkova
On the Embeddings of Variables in Recurrent Neural Networks for Source Code. NAACL-HLT (2021)
Nadezhda Chirkova, Sergey Troshin
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code. CoRR (2020)
Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov
Structured Sparsification of Gated Recurrent Neural Networks. AAAI (2020)
Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov
On Power Laws in Deep Ensembles. NeurIPS (2020)
Nadezhda Chirkova, Sergey Troshin
Empirical Study of Transformers for Source Code. CoRR (2020)
Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov
On Power Laws in Deep Ensembles. CoRR (2020)
Nadezhda Chirkova
Neural Code Completion with Anonymized Variable Names. CoRR (2020)
Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? CoRR (2020)
Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov
Structured Sparsification of Gated Recurrent Neural Networks. CoRR (2019)
Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
Bayesian Compression for Natural Language Processing. CoRR (2018)
Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
Bayesian Compression for Natural Language Processing. EMNLP (2018)
Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov
Bayesian Sparsification of Gated Recurrent Neural Networks. CoRR (2018)
Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov
Bayesian Sparsification of Recurrent Neural Networks. CoRR (2017)