Analyzing the potential of using large language models for languages of peoples of the Russian Federation and the CIS in the modern digital space

被引：0

作者：

Novikova, Marina L. ^{[1
]}

Novikov, Phillip N. ^{[2
]}

机构：

[1] Peoples Friendship Univ Russia, Russian Language & Cultural Studies Dept, Moscow, Russia

[2] Peoples Friendship Univ Russia, Foreign Languages Dept, Moscow, Russia

来源：

FILOLOGICHESKIE NAUKI-NAUCHNYE DOKLADY VYSSHEI SHKOLY-PHILOLOGICAL SCIENCES-SCIENTIFIC ESSAYS OF HIGHER EDUCATION | 2023年 / 06期

关键词：

artificial intelligence; machine learning; languages of the peoples of Russia; large language models;

D O I：

10.20339/PhS.6s-23.003

中图分类号：

H [语言、文字];

学科分类号：

05 ;

摘要：

In the timeframe from 2022 to 2023, the progress in the development of large language models, based on machine learning and neural network technologies, also referred to as "artificial intelligence", reached an unprecedented level. This facilitated making a significant leap for the application of natural language processing algorithms to both science and everyday life. The article examines the potential and current challenges of using these technologies with respect to the languages of the peoples of the Russian Federation and the CIS in the modern digital environment. The study touches upon such areas as translation, linguistic analysis, language popularization, and development of original language online services.

引用

页码：3 / 11

页数：9

共 25 条

[1] Monitoring the condition and use of the Russian language and other languages of the peoples of the Russian Federation
Marusenko, Mikhail A.
Marusenko, Natalya M.
Avlova, Tatyana B.
Grebennikov, Alexander O.
Kusal, Krzysztof
FILOLOGICHESKIE NAUKI-NAUCHNYE DOKLADY VYSSHEI SHKOLY-PHILOLOGICAL SCIENCES-SCIENTIFIC ESSAYS OF HIGHER EDUCATION, 2021, (06): : 32 - 43
[2] Analyzing the Innovative Potential of Texts Generated by Large Language Models: An Empirical Evaluation
Krauss, Oliver
Jungwirth, Michaela
Elflein, Marius
Sandler, Simone
Altenhofer, Christian
Stoeck, Andreas
DATABASE AND EXPERT SYSTEMS APPLICATIONS - DEXA 2023 WORKSHOPS, 2023, 1872 : 11 - 22
[3] VERIFICATION OF THE DIGITAL DEVICES MODELS REPRESENTED IN THE LANGUAGE USING HARDWARE DESCRIPTION LANGUAGES
Krivulya, G. F.
Syrevich, E. E.
Karasev, A. L.
RADIO ELECTRONICS COMPUTER SCIENCE CONTROL, 2005, 2 : 63 - 68
[4] Investigating the Potential of Using Large Language Models for Scheduling
Jobson, Deddy
Li, Yilin
PROCEEDINGS OF THE 1ST ACM INTERNATIONAL CONFERENCE ON AI-POWERED SOFTWARE, AIWARE 2024, 2024, : 170 - 171
[5] Digital Diagnostics: The Potential of Large Language Models in Recognizing Symptoms of Common Illnesses
Gupta, Gaurav Kumar
Singh, Aditi
Manikandan, Sijo Valayakkad
Ehtesham, Abul
AI, 2025, 6 (01)
[6] Exploring the potential of large language models for improving digital forensic investigation efficiency
Wickramasekara, Akila
Breitinger, Frank
Scanlon, Mark
FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION, 2025, 52
[7] Exploring the potential of large language models for author profiling tasks in digital text forensics
Cho, Sang-Hyun
Kim, Dohyun
Kwon, Hyuk-Chul
Kim, Minho
FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION, 2024, 50
[8] DecoMT: Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models
Puduppully, Ratish
Kunchukuttan, Anoop
Dabre, Raj
Aw, Ai Ti
Chen, Nancy F.
2023 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, EMNLP 2023, 2023, : 4586 - 4602
[9] Using Large Language Models for Adaptive Dialogue Management in Digital Telephone Assistants
Soliman, Hassan
Kravcik, Milos
Basvoju, Nagasandeepa
Jaehnichen, Patrick
ADJUNCT PROCEEDINGS OF THE 32ND ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION, UMAP 2024, 2024, : 399 - 405
[10] Exploring the Potential of Large Language Models in Neurology, Using Neurologic Localization as an Example
Chiang, Chia-Chun
Fries, Jason A.
NEUROLOGY-CLINICAL PRACTICE, 2024, 14 (03)

← 1 2 3 →