?
JavaCapsule: Итеративная генерация и отладка Java-кода на основе структурированной обратной связи
С. 73–90.
Alexandrov D., Vasilevsky V., Rezunik L., Kuligin L., Manushkina A., Думкин Н. А., Прозорский М. А., Пинигин К. Ю.
Sherstinova T., Урих А. Е., Вестник Новосибирского государственного университета. Серия: Лингвистика и межкультурная коммуникация 2026 Т. 24 № 2 С. 42–54
Цифровые технологии XXI века способствуют формированию новых методологических подходов в гуманитарных науках, включая литературоведение и биографические исследования. Для автоматизации процессов сбора и аннотирования информации все чаще используют большие языковые модели (Large Language Models, LLM), включая ChatGPT. Развитие подобных инструментов стимулирует переход от традиционных методологических подходов, основанных на исключительно ручном аннотировании и экспертной верификации, к гибридным, ...
Added: September 28, 2026
Shipovalova L., Asya A. Filatova, Социология власти 2026 Vol. 38 No. 1 P. 224–243
This article examines the integration of large language model based chatbots into educational practices in Russian higher education through the lens of critical theory and curriculum ideologies. Drawing on Ivan Illich’s concept of convivial tools and Jürgen Habermas’s distinction between instrumental and communicative rationality, the authors conceptualize large language models as technologies capable of operating ...
Added: September 18, 2026
Karpenko I., Человек 2026 Т. 37 № 5 С. 42–58
This article examines the question of agency in artificial intelligence systems. A distinction is proposed between three types of agency: ontological, functional, and ascribed. The central thesis is that functional agency is a genuine rather than metaphorical type, which is grounded through the teleological theory of function and through a critique of the argument from ...
Added: September 16, 2026
Rezunik L., Alexandrov D., Mikhail Prozorskiy, , in: Intelligent Decision Technologies. Proceedings of the 17th KES-IDT 2025 ConferenceVol. 450.: Cham: Springer, 2026. P. 81–91.
Multi-Agent Systems (MAS) can benefit from Large Language Models (LLMs), but hallucinations pose risks to decision-making. This paper introduces an approach for creating MAS based on LLMs and proposes a generalized architecture for such systems. We ensure that reasoning is conducted through predicate logic to minimize errors, and LLMs are exclusively utilized to translate natural ...
Added: September 14, 2026
Egorova I. S., Journal of Employment and Career 2025 Vol. 4 No. 4 P. 27–43
Background. The rapid diffusion of large language models has intensified claims that professional translation is approaching technological redundancy. The available evidence, however, is dispersed across labour economics, computational linguistics, translation stu-dies, industry research, and translator education, and it does not support a uniform conclu-sion for the profession as a whole.Purpose. This article examines how artificial ...
Added: September 8, 2026
Джонов А. Т., Avdoshin S. M., Информационные технологии 2026 Т. 32 № 8 С. 421–427
This systematic review presents an analysis of the "Vibe Coding" methodology — a contemporary approach to the iterative software development process using Large Language Models (LLMs). Code generation tools are transforming software development by enabling programmers to formulate tasks and describe the desired behavior of software in natural language, while LLMs generate source code corresponding ...
Added: August 25, 2026
Rozhkova K., Roshchin S., Roshchina Y., Вопросы экономики 2026 № 8 С. 29–54
Стремительное развитие генеративного искусственного интеллекта (генИИ) усилило дискуссии о том, как новые технологии трансформируют рынок труда, особенно позиции и задачи, которые еще недавно мог выполнять только человек. Эксперименты показывают, что генеративный ИИ может обеспечить значительный прирост производительности, особенно менее квалифицированных сотрудников, что может приводить к возникновению индивидуальной зарплатной отдачи на рынке труда. Впервые для России ...
Added: August 11, 2026
Surkov A., Ignatenko V., Koltsov S., Computers, Materials and Continua 2026 Vol. 88 No. 3 Article 74
Large language models have recently demonstrated promising capabilities in mathematical reasoning; however, their performance on tasks requiring strict symbolic manipulation, such as solving differential equations, remains limited, especially for compact models. In this work, we investigate whether activation steering combined with reinforcement learning can improve the quality of solutions generated by pretrained language models without ...
Added: July 8, 2026
Джейранян А. Д., Ларионова Я. А., Lyadova L. N., В кн.: ГрафиКон 2025 : материалы 35-й Международной конференции по компьютерной графике и машинному зрению (Россия, Йошкар-Ола, 30 сентября – 2 октября 2025 г.).: Йошкар-Ола: Поволжский государственный технологический университет, 2025. С. 353–366.
Abstract. Data visualization tools are key analytics tools that make it easier to identify dependencies, trends, and patterns. These tools are used by a broad range of specialists (analysts, scientists, business leaders, managers, teachers, and specialists in other fields where accurate and understandable presentation of information is critically important to improve the effectiveness of data ...
Added: May 5, 2026
Подболотова М. И., Адамский А. И., Kolachev N. et al., Высшее образование в России 2026 Т. 35 № 4 С. 21–35
The purpose of the article is to present and justify a pedagogical model of personal
ized feedback based on large language models (LLM) for the educational process in a human
ities-oriented master’s program. The relevance of the study is determined by the objectives of
digital transformation of higher education in the Russian Federation, outlined in Presidential
Decree No. 474 ...
Added: May 4, 2026
Baysha O., Trofimov V., Российская школа связей с общественностью 2026 № 40 С. 171–191
A growing number of scholars are warning about the dangers of the reproduction by generative AI of socio-political and ideological biases absorbed by models from the texts on which they were trained. If a given model was trained on Western media texts, it may generate narratives that reproduce West centric views of world events. This ...
Added: April 21, 2026
Seredkina E., Seletkova G., Mikhailovsky A., Technology and Language 2026 Vol. 7 No. 1 P. 63–79
The rapid diffusion of Large Language Models (LLMs) into socially and politically sensitive domains raises critical questions about the nature and origins of political bias in artificial intelligence. While existing research often treats bias as a technical flaw to be minimized, this article advances a broader philosophical and cultural interpretation of LLM bias as an ...
Added: April 1, 2026
Андрющенко Г. Д., Godunova M., Иванов В. В. et al., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2025 Т. 527 С. 320–331
Large language models (LLMs) pretrained on English-centered corpora have biases and perform sub-optimally on other natural languages. Adaptation of LLMs vocabulary provides a resource-efficient way to improve the quality of a pretrained model. Previously proposed adaptation techniques focus on performance (accuracy) and size metrics (fertility), ignoring other aspects in comparison, such as inference latency, compute ...
Added: January 15, 2026
Vasilevsky V., Alexandrov D., Proceedings of the Institute for System Programming of the RAS 2025 Vol. 37 No. 5 P. 173–182
Automatic code generation by large language models (LLMs) has achieved significant success, yet
it still faces challenges when dealing with complex and large codebases, especially in languages like Java. The
limitations of LLM context windows and the complexity of debugging generated code are key obstacles. This
paper presents an approach aimed at improving Java code generation and debugging. ...
Added: December 26, 2025
Balakina Y. V., Grigoreva M., Соколова Е. Н., Вестник Российского фонда фундаментальных исследований. Гуманитарные и общественные науки 2025 Т. 123 № 4 С. 56–69
The article examines the potential of large language models (LLMs) for automated analysis of value-laden and patriotic discourse in Russian-language social media. Using a corpus of posts from VK, Odnoklassniki and Telegram (2023–2025), it investigates the extent to which automatic coding results align with expert annotation based on a specially developed categorical scheme. The codebook ...
Added: November 26, 2025
Anton R., Mikhalchuk M., Rahmatullaev T. et al., , in: Findings of the Association for Computational Linguistics: NAACL 2025.: Association for Computational Linguistics, 2025. P. 7757–7764.
We introduce methods to quantify how Large Language Models (LLMs) encode and store contextual information, revealing that tokens often seen as minor (e.g., determiners, punctuation) carry surprisingly high context. Notably, removing these tokens — especially stopwords, articles, and commas — consistently degrades performance on MMLU and BABILong-4k, even if removing only irrelevant tokens. Our analysis ...
Added: November 6, 2025
Parshakov P., Paklina S., Matkin N. et al., Вестник Пермского университета. Серия: Экономика 2026 Т. 21 № 1 С. 42–57
Introduction. Large language Models (LLM) are increasingly being used in social sciences to simulate the behavior of experimental participants and analyze norms of cooperation and justice. However, the question remains whether they are capable of reproducing social asymmetries, including gender differences. Goal. The work aims to test whether LLM reproduces gender differences in the Dictator ...
Added: October 27, 2025
Shenkman E., Parshakov P., Matkin N., Журнал Новой экономической ассоциации 2026 № 2(71) С. 177–203
This article analyzes the behavior of large language models (LLMs) in the Dictator game; the comparison was carried out against the results of previously conducted laboratory behavioral experiments with human participants. The study examines modifications of the basic game, that include the possibility of taking resources from the opponent as well as the introduction of ...
Added: October 27, 2025
Krokhin A., Гусев М. М., Программные системы и вычислительные методы 2025 № 2
The article addresses the issue of prompt obfuscation as a means of circumventing protective mechanisms in large language models (LLMs) designed to detect prompt injections. Prompt injections represent a method of attack in which malicious actors manipulate input data to alter the model's behavior and cause it to perform undesirable or harmful actions. Obfuscation involves ...
Added: October 4, 2025
Maksimenkova O. V., Сегал А. П., Вопросы философии 2025 № 10 С. 67–76
The study is devoted to the humans and artificial intelligence (AI) interaction. The authors view this interaction as mediated by interfaces that both simplify it and hide the real mechanisms of encoding and decoding messages (according to Shannon). In such a situation, the characteristics of the actor of communication are blurred, and it is not ...
Added: October 2, 2025
Skrynnikova I. V., Когнитивные исследования языка 2024 Т. 2 № 58 С. 638–642
В статье обосновывается важность разрешения проблемы интерпретации в LLM метафорического языка как уникального человеческого способа самовыражения на основе мышления по аналогии.Вопрос о том, как научить систему автоматически понимать метафору и наделить ее способностью делать инференции, до сих пор остается открытым.Выявлено, что неспособность систем ИИ мыслить по аналогии ввиду отсутствия у них физического тела, неумене делать ...
Added: August 28, 2025
Victoria I. Firsanova, Вестник Череповецкого государственного университета 2025 Vol. 124 No. 1 P. 80–90
The paper proposes a novel approach to the verification of linguistic hypotheses applying large language models. The method uses a formal description of a linguistic theory to be proven to build a vector representation for a collection of language data. The representation is compared with embeddings constructed with help of neural network models. The research ...
Added: July 10, 2025