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ПРИМЕНЕНИЕ СТИЛОМЕТРИИ ДЛЯ ОПРЕДЕЛЕНИЯ СГЕНЕРИРОВАННЫХ ТЕКСТОВ
С. 176–182.
Е. А. Сальников, А. А. Бонч-Осмоловская
In book
Сибирский федеральный университет, 2023.
Surkov A., Ignatenko V., Koltcov Sergei, Computers, Materials and Continua 2026
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
Buzaev F., Mullakhmetov R., Bogachev R. et al., Association for Computational Linguistics, 2026.
Playlist generation based on textual queries using large language models (LLMs) is becoming an important interaction paradigm for music streaming platforms. User queries span a wide spectrum from highly personalized intent to essentially catalog-style requests. Existing systems typically rely on non-personalized retrieval/ranking or apply a fixed level of preference conditioning to every query, which can ...
Added: June 22, 2026
Dmitry Pronin, Evgeny Kazartsev, Digital Scholarship in the Humanities 2026 P. 1–15
This article repositions Burrows’s Delta as a flexible family of distance measures for exploratory and unsupervised stylometry, where interpretability and stability are as important as predictive accuracy. We introduce two probabilistic extensions, Rank-Turbulence Delta and Jensen–Shannon Delta, by reinterpreting uncentred standardized word-frequency vectors as non-negative representations that can be normalized into probability distributions and compared ...
Added: June 4, 2026
Parkina U., Rakhuba M., , in: 39th Conference on Neural Information Processing Systems (NeurIPS 2025).: NeurIPS, 2025. P. 71014–71041.
Recent studies suggest that context-aware low-rank approximation is a useful tool for compression and fine-tuning of modern large-scale neural networks. In this type of approximation, a norm is weighted by a matrix of input activations, significantly improving metrics over the unweighted case. Nevertheless, existing methods for neural networks suffer from numerical instabilities due to their ...
Added: April 29, 2026
СПб.: Санкт-Петербургский Федеральный исследовательский центр РАН, 2025.
Двадцать вторая Национальная конференция по искусственному интеллекту с международным участием КИИ-2025 продолжает традицию советских (российских) конференций, организуемых Российской ассоциацией искусственного интеллекта. В первом томе трудов публикуются пленарные доклады и доклады участников конференции, представленные на следующих секциях: Секция 1 «Инженерия знаний», Секция 2 «Интеллектуальный анализ данных», Секция 3 «Моделирование рассуждений», Секция 4 «Интеллектуальный анализ текстов, большие ...
Added: February 15, 2026
Василевский В. И., 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
Малинов С. А., Галактика медиа: журнал медиа исследований 2025 Т. 7 № 4 С. 154–173
In recent years, artificial intelligence (AI) has been actively integrated into everyday human life. Its popularity continues to grow steadily, and companies increasingly employ AI to optimize and accelerate workflows. Ordinary users leverage large language models (LLMs) and multimodal AI systems to perform a wide range of tasks, including generating texts, images, and videos; planning ...
Added: December 7, 2025
Komissarenko A., Voloshina E., Чевелева А. Н. et al., Scientific data 2025 Vol. 12 No. 1 Article 1687
Recently, the idea of brain-model alignment has been the topic of several influential works. However, most of previous studies were based on datasets collected during regular reading tasks where the subjects were not exposed to processing linguistic incongruencies, and stimuli were not controlled for key linguistic properties. Meanwhile, interpretability studies of Large Language Models pay ...
Added: November 18, 2025
Solovev G. V., Zhidkovskaya A. B., Orlova A. et al., , in: Findings of the Association for Computational Linguistics: EMNLP 2025.: Association for Computational Linguistics, 2025. Ch. 367 P. 6956–6998.
Hit identification is a central challenge in early drug discovery, traditionally requiring substantial experimental resources. Recent advances in artificial intelligence, particularly large language models (LLMs), have enabled virtual screening methods that reduce costs and improve efficiency. However, the growing complexity of these tools has limited their accessibility to wet-lab researchers. Multi-agent systems offer a promising ...
Added: November 16, 2025
Sviridov I., Miftakhova A., Tereshchenko A. et al., , in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP).: Association for Computational Linguistics, 2025. Ch. 1353 P. 26625–26665.
Though Large Vision-Language Models (LVLMs) are being actively explored in medicine, their ability to conduct complex real-world telemedicine consultations combining accurate diagnosis with professional dialogue remains underexplored. This paper presents 3MDBench (Medical Multimodal Multi-agent Dialogue Benchmark), an open-source framework for simulating and evaluating LVLM-driven telemedical consultations. 3MDBench simulates patient variability through temperament-based Patient Agent and evaluates diagnostic accuracy and dialogue quality ...
Added: November 16, 2025
Zmushko P., Beznosikov A., Takáč M. et al., , in: Volume 267: International Conference on Machine Learning, 13-19 July 2025, Vancouver Convention Center, Vancouver, CanadaVol. 267.: [б.и.], 2025. P. 80708–80739.
With the increase in the number of parameters in large language models, the training process increasingly demands larger volumes of GPU memory. A significant portion of this memory is typically consumed by the optimizer state. To overcome this challenge, recent approaches such as low-rank adaptation (LoRA), low-rank gradient projection (GaLore), and blockwise optimization (BAdam) have ...
Added: November 10, 2025
Rodionov G., Roman Garipov, Alina Shutova et al., , in: 39th Conference on Neural Information Processing Systems (NeurIPS 2025).: NeurIPS, 2025. P. 46592–46633.
Large Language Models (LLMs) have demonstrated the ability to tackle increasingly complex tasks through advanced reasoning, long-form content generation, and tool use. Solving these tasks often involves long inference-time computations. In human problem solving, a common strategy to expedite work is collaboration: by dividing the problem into sub-tasks, exploring different strategies concurrently, etc. Recent research ...
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
Шенкман Евгения Андреевна, 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
Ignatenko V., Surkov A., Zakharov V. et al., Sci 2025 Vol. 7 No. 3 Article 130
Large language models (LLMs) have recently demonstrated remarkable capabilities in natural language processing, mathematical reasoning, and code generation. However, their potential for solving differential equations—fundamental to applied mathematics, physics, and engineering—remains insufficiently explored. For the first time, we applied LLMs as translators from the textual form of an equation into the textual representation of its ...
Added: October 10, 2025
Surkov A., Zakharov V., Sergei Koltcov et al., , in: Smart Technologies, Systems and Applications: 4th International Conference, SmartTech-IC 2024, Quito, Ecuador, December 2–4, 2024, Revised Selected Papers, Part IIVol. 2: Revised Selected Papers, Part II.: Springer, 2025. P. 239–252.
Currently, large language models are actively developing and beginning to be used to solve some mathematical problems. With the emergence of xLSTM model, which demonstrates the results comparable with transformer-based models, there has been a surge of interest in recurrent neural networks. This paper considers the application of baseline recurrent models such as LSTM and ...
Added: September 11, 2025
Alieva O., Вестник Православного Свято-Тихоновского гуманитарного университета. Серия 3: Филология 2025 Т. 84 С. 54–85
Despite the criticism, the standard chronology of Plato’s works continues to hold sway not only over “developmentalists”, but also over various types of “unitarians”. The authority of the standard chronology rests on the confidence that the division of the dialogues into three groups has been “proven” with quantitative methods. In addition to the general theoretical ...
Added: August 28, 2025