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ORCIDNadezhda Chirkova
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2020 – today
- 2024
[c12]Nadezhda Chirkova, Vassilina Nikoulina:
Zero-shot cross-lingual transfer in instruction tuning of large language models. INLG 2024: 695-708- [c11]Nadezhda Chirkova, Vassilina Nikoulina:
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks. NAACL-HLT 2024: 7222-7238 - [i22]Nadezhda Chirkova, Vassilina Nikoulina:
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks. CoRR abs/2402.12279 (2024) - [i21]Nadezhda Chirkova, Vassilina Nikoulina:
Zero-shot cross-lingual transfer in instruction tuning of large language model. CoRR abs/2402.14778 (2024) - [i20]David Rau, Hervé Déjean, Nadezhda Chirkova, Thibault Formal, Shuai Wang, Vassilina Nikoulina, Stéphane Clinchant:
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation. CoRR abs/2407.01102 (2024) - [i19]Nadezhda Chirkova, Vassilina Nikoulina, Jean-Luc Meunier, Alexandre Bérard:
Investigating the potential of Sparse Mixtures-of-Experts for multi-domain neural machine translation. CoRR abs/2407.01126 (2024) - [i18]Nadezhda Chirkova, David Rau, Hervé Déjean, Thibault Formal, Stéphane Clinchant, Vassilina Nikoulina:
Retrieval-augmented generation in multilingual settings. CoRR abs/2407.01463 (2024) - 2023
- [c10]Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman:
Should you marginalize over possible tokenizations? ACL (2) 2023: 1-12 - [c9]Nadezhda Chirkova, Sergey Troshin:
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code. ICLR 2023 - [i17]Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman:
Should you marginalize over possible tokenizations? CoRR abs/2306.17757 (2023) - [i16]Nadezhda Chirkova, Sergey Troshin:
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code. CoRR abs/2308.00683 (2023) - [i15]Nadezhda Chirkova, Sheng Liang, Vassilina Nikoulina:
Empirical study of pretrained multilingual language models for zero-shot cross-lingual generation. CoRR abs/2310.09917 (2023) - 2022
- [c8]Sergey Troshin, Nadezhda Chirkova:
Probing Pretrained Models of Source Codes. BlackboxNLP@EMNLP 2022: 371-383 - [i14]Sergey Troshin, Nadezhda Chirkova:
Probing Pretrained Models of Source Code. CoRR abs/2202.08975 (2022) - [i13]Shamil Ayupov, Nadezhda Chirkova:
Parameter-Efficient Finetuning of Transformers for Source Code. CoRR abs/2212.05901 (2022) - 2021
- [c7]Nadezhda Chirkova, Sergey Troshin:
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code. NAACL-HLT 2021: 278-288 - [c6]Nadezhda Chirkova:
On the Embeddings of Variables in Recurrent Neural Networks for Source Code. NAACL-HLT 2021: 2679-2689 - [c5]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: 21545-21556 - [c4]Nadezhda Chirkova
, Sergey Troshin:
Empirical study of transformers for source code. ESEC/SIGSOFT FSE 2021: 703-715 - [i12]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 abs/2106.15739 (2021) - [i11]Ildus Sadrtdinov, Nadezhda Chirkova, Ekaterina Lobacheva:
On the Memorization Properties of Contrastive Learning. CoRR abs/2107.10143 (2021) - [i10]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 abs/2112.14423 (2021) - 2020
- [c3]Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov:
Structured Sparsification of Gated Recurrent Neural Networks. AAAI 2020: 4989-4996 - [c2]Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov:
On Power Laws in Deep Ensembles. NeurIPS 2020 - [i9]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? CoRR abs/2005.07292 (2020) - [i8]Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov:
On Power Laws in Deep Ensembles. CoRR abs/2007.08483 (2020) - [i7]Nadezhda Chirkova, Sergey Troshin:
Empirical Study of Transformers for Source Code. CoRR abs/2010.07987 (2020) - [i6]Nadezhda Chirkova, Sergey Troshin:
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code. CoRR abs/2010.12663 (2020) - [i5]Nadezhda Chirkova:
Neural Code Completion with Anonymized Variable Names. CoRR abs/2010.12693 (2020)
2010 – 2019
- 2019
- [i4]Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov:
Structured Sparsification of Gated Recurrent Neural Networks. CoRR abs/1911.05585 (2019) - 2018
- [c1]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Bayesian Compression for Natural Language Processing. EMNLP 2018: 2910-2915 - [i3]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Bayesian Compression for Natural Language Processing. CoRR abs/1810.10927 (2018) - [i2]Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov:
Bayesian Sparsification of Gated Recurrent Neural Networks. CoRR abs/1812.05692 (2018) - 2017
- [i1]Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov:
Bayesian Sparsification of Recurrent Neural Networks. CoRR abs/1708.00077 (2017)
Coauthor Index
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last updated on 2024-09-25 01:37 CEST by the dblp team
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