Maria Tikhonova

Orcid: 0000-0003-4561-5415

According to our database1, Maria Tikhonova authored at least 17 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
mGPT: Few-Shot Learners Go Multilingual.
Trans. Assoc. Comput. Linguistics, 2024

The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design.
CoRR, 2024

Long Input Benchmark for Russian Analysis.
CoRR, 2024

MERA: A Comprehensive LLM Evaluation in Russian.
CoRR, 2024

A Family of Pretrained Transformer Language Models for Russian.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024


2023
Ad astra or astray: Exploring linguistic knowledge of multilingual BERT through NLI task - CORRIGENDUM.
Nat. Lang. Eng., July, 2023

Ad astra or astray: Exploring linguistic knowledge of multilingual BERT through NLI task.
Nat. Lang. Eng., May, 2023

A Family of Pretrained Transformer Language Models for Russian.
CoRR, 2023

Static, Dynamic, or Contextualized: What is the Best Approach for Discovering Semantic Shifts in Russian Media?
Proceedings of the Analysis of Images, Social Networks and Texts, 2023

On the Way to Controllable Text Summarization in Russian.
Proceedings of the Recent Trends in Analysis of Images, Social Networks and Texts, 2023

2022
Russian SuperGLUE 1.1: Revising the Lessons not Learned by Russian NLP models.
CoRR, 2022

TAPE: Assessing Few-shot Russian Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
MOROCCO: Model Resource Comparison Framework.
CoRR, 2021

Continuous Prompt Tuning for Russian: How to Learn Prompts Efficiently with RuGPT3?
Proceedings of the Recent Trends in Analysis of Images, Social Networks and Texts, 2021

2020
RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Text Mining for Evaluation of Candidates Based on Their CVs.
Proceedings of the Analysis of Images, Social Networks and Texts, 2019


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