Viktoria Chekalina

According to our database, Viktoria Chekalina authored at least 18 papers between 2018 and 2026.

Collaborative distances:

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

2026

Acceleration of Backpropagation in Linear Layers of Transformer Models Based on Gradient Structure.

Dmitrii Topchii, Alexander Panchenko, Viktoria Chekalina

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

Fast and Accurate Fisher-Guided Quantization via Efficient Kronecker Factorization.

Viktoriia Chekalina, Gerasin Timofey, Andrey Kuznetsov, Evgeny Frolov

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Generalized Fisher-Weighted SVD: Scalable Kronecker-Factored Fisher Approximation for Compressing Large Language Models.

Viktoriia Chekalina, Daniil Moskovskiy, Daria Cherniuk, Maxim Kurkin, Andrey Kuznetsov, Evgeny Frolov

CoRR, May, 2025

2024

Addressing Hallucinations in Language Models with Knowledge Graph Embeddings as an Additional Modality.

Viktoriia Chekalina, Anton Razzigaev, Elizaveta Goncharova, Andrey Kuznetsov

CoRR, 2024

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers.

Viktoria Chekalina, Anna Rudenko, Gleb Mezentsev, Alexander Mikhalev, Alexander Panchenko, Ivan V. Oseledets

CoRR, 2024

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers.

Viktoria Chekalina, Anna Rudenko, Gleb Mezentsev, Aleksandr Mikhalev, Alexander Panchenko, Ivan V. Oseledets

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Efficient GPT Model Pre-training using Tensor Train Matrix Representation.

Viktoria Chekalina, Georgii S. Novikov, Julia Gusak, Ivan V. Oseledets, Alexander Panchenko

CoRR, 2023

Retrieving Comparative Arguments using Ensemble Methods and Neural Information Retrieval.

Viktoria Chekalina, Alexander Panchenko

CoRR, 2023

A Computational Study of Matrix Decomposition Methods for Compression of Pre-trained Transformers.

Sergey Pletenev, Viktoria Chekalina, Daniil Moskovskiy, Mikhail Seleznev, Sergey Zagoruyko, Alexander Panchenko

Proceedings of the 37th Pacific Asia Conference on Language, 2023

Efficient GPT Model Pre-training using Tensor Train Matrix Representation.

Viktoria Chekalina, Georgiy Novikov, Julia Gusak, Alexander Panchenko, Ivan V. Oseledets

Proceedings of the 37th Pacific Asia Conference on Language, 2023

Transformers Compression: A Study of Matrix Decomposition Methods Using Fisher Information.

Sergey Pletenev, Daniil Moskovskiy, Viktoria Chekalina, Mikhail Seleznyov, Sergey Zagoruyko, Alexander Panchenko

Proceedings of the Analysis of Images, Social Networks and Texts, 2023

2022

MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering.

Viktoria Chekalina, Anton Razzhigaev, Albert Sayapin, Alexander Panchenko

CoRR, 2022

Retrieving Comparative Arguments using Deep Language Models.

Viktoria Chekalina, Alexander Panchenko

Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022

MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering.

Viktoria Chekalina, Anton Razzhigaev, Albert Sayapin, Evgeny Frolov, Alexander Panchenko

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2022

2021

Which is Better for Deep Learning: Python or MATLAB? Answering Comparative Questions in Natural Language.

Viktoria Chekalina, Alexander Bondarenko, Chris Biemann, Meriem Beloucif, Varvara Logacheva, Alexander Panchenko

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, 2021

Retrieving Comparative Arguments using Ensemble Methods and BERT.

Viktoria Chekalina, Alexander Panchenko

Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum, Bucharest, Romania, September 21st - to, 2021

2020

Retrieving Comparative Arguments using Deep Pre-trained Language Models and NLU.

Viktoria Chekalina, Alexander Panchenko

Proceedings of the Working Notes of CLEF 2020, 2020

2018

Generative Models for Fast Calorimeter Simulation.LHCb case.

Viktoria Chekalina, Elena Orlova, Fedor Ratnikov, Dmitry Ulyanov, Andrey Ustyuzhanin, Egor Zakharov

CoRR, 2018