Zobrazeno 1 - 10
of 209
pro vyhledávání: '"Tikhonova, Maria A."'
Embedding models play a crucial role in Natural Language Processing (NLP) by creating text embeddings used in various tasks such as information retrieval and assessing semantic text similarity. This paper focuses on research related to embedding mode
Externí odkaz:
http://arxiv.org/abs/2408.12503
Autor:
Churin, Igor, Apishev, Murat, Tikhonova, Maria, Shevelev, Denis, Bulatov, Aydar, Kuratov, Yuri, Averkiev, Sergej, Fenogenova, Alena
Recent advancements in Natural Language Processing (NLP) have fostered the development of Large Language Models (LLMs) that can solve an immense variety of tasks. One of the key aspects of their application is their ability to work with long text doc
Externí odkaz:
http://arxiv.org/abs/2408.02439
Autor:
Fenogenova, Alena, Chervyakov, Artem, Martynov, Nikita, Kozlova, Anastasia, Tikhonova, Maria, Akhmetgareeva, Albina, Emelyanov, Anton, Shevelev, Denis, Lebedev, Pavel, Sinev, Leonid, Isaeva, Ulyana, Kolomeytseva, Katerina, Moskovskiy, Daniil, Goncharova, Elizaveta, Savushkin, Nikita, Mikhailova, Polina, Dimitrov, Denis, Panchenko, Alexander, Markov, Sergei
Over the past few years, one of the most notable advancements in AI research has been in foundation models (FMs), headlined by the rise of language models (LMs). As the models' size increases, LMs demonstrate enhancements in measurable aspects and th
Externí odkaz:
http://arxiv.org/abs/2401.04531
Autor:
Zmitrovich, Dmitry, Abramov, Alexander, Kalmykov, Andrey, Tikhonova, Maria, Taktasheva, Ekaterina, Astafurov, Danil, Baushenko, Mark, Snegirev, Artem, Kadulin, Vitalii, Markov, Sergey, Shavrina, Tatiana, Mikhailov, Vladislav, Fenogenova, Alena
Transformer language models (LMs) are fundamental to NLP research methodologies and applications in various languages. However, developing such models specifically for the Russian language has received little attention. This paper introduces a collec
Externí odkaz:
http://arxiv.org/abs/2309.10931
Autor:
Taktasheva, Ekaterina, Shavrina, Tatiana, Fenogenova, Alena, Shevelev, Denis, Katricheva, Nadezhda, Tikhonova, Maria, Akhmetgareeva, Albina, Zinkevich, Oleg, Bashmakova, Anastasiia, Iordanskaia, Svetlana, Spiridonova, Alena, Kurenshchikova, Valentina, Artemova, Ekaterina, Mikhailov, Vladislav
Recent advances in zero-shot and few-shot learning have shown promise for a scope of research and practical purposes. However, this fast-growing area lacks standardized evaluation suites for non-English languages, hindering progress outside the Anglo
Externí odkaz:
http://arxiv.org/abs/2210.12813
Autor:
Shliazhko, Oleh, Fenogenova, Alena, Tikhonova, Maria, Mikhailov, Vladislav, Kozlova, Anastasia, Shavrina, Tatiana
Recent studies report that autoregressive language models can successfully solve many NLP tasks via zero- and few-shot learning paradigms, which opens up new possibilities for using the pre-trained language models. This paper introduces two autoregre
Externí odkaz:
http://arxiv.org/abs/2204.07580
Autor:
Fenogenova, Alena, Tikhonova, Maria, Mikhailov, Vladislav, Shavrina, Tatiana, Emelyanov, Anton, Shevelev, Denis, Kukushkin, Alexandr, Malykh, Valentin, Artemova, Ekaterina
In the last year, new neural architectures and multilingual pre-trained models have been released for Russian, which led to performance evaluation problems across a range of language understanding tasks. This paper presents Russian SuperGLUE 1.1, an
Externí odkaz:
http://arxiv.org/abs/2202.07791
Autor:
Malykh, Valentin, Kukushkin, Alexander, Artemova, Ekaterina, Mikhailov, Vladislav, Tikhonova, Maria, Shavrina, Tatiana
The new generation of pre-trained NLP models push the SOTA to the new limits, but at the cost of computational resources, to the point that their use in real production environments is often prohibitively expensive. We tackle this problem by evaluati
Externí odkaz:
http://arxiv.org/abs/2104.14314
Autor:
Tikhonova, Maria A.1,2 (AUTHOR) olesya_ter@bionet.nsc.ru, Shoeva, Olesya Y.1 (AUTHOR) amstislavskayatg@neuronm.ru, Tenditnik, Michael V.2 (AUTHOR), Akopyan, Anna A.2 (AUTHOR), Litvinova, Ekaterina A.2 (AUTHOR), Popova, Nelly A.1,3 (AUTHOR), Amstislavskaya, Tamara G.1,2,3 (AUTHOR), Khlestkina, Elena K.1,4 (AUTHOR) tikhonovama@neuronm.ru
Publikováno v:
International Journal of Molecular Sciences. Jun2024, Vol. 25 Issue 11, p5727. 17p.
Autor:
Shavrina, Tatiana, Fenogenova, Alena, Emelyanov, Anton, Shevelev, Denis, Artemova, Ekaterina, Malykh, Valentin, Mikhailov, Vladislav, Tikhonova, Maria, Chertok, Andrey, Evlampiev, Andrey
In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE. Recent advances in the field of universal language models and transformers require the development of a methodology for their broad di
Externí odkaz:
http://arxiv.org/abs/2010.15925