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News
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.
September 17, 2026
'I Wish That People Would Place Greater Trust in Science'
When Tatiana Eremicheva chose Fundamental and Computational Linguistics as her field of study, she thought it would be about learning languages. Instead, she discovered it was about helping people. In this interview for the HSE Young Scientists project, she discusses science as a way of understanding the world, billiards as a team-building activity, and why learning to read is not always as easy as it seems.
September 15, 2026
Immunity to Chaos: How Personal Resources Help Us Cope with the Challenges of a Turbulent World
International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?

 

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XXII национальная конференция по искусственному интеллекту с международным участием (КИИ-2025)

Т. 1. СПб. : Санкт-Петербургский Федеральный исследовательский центр РАН, 2025.
Chapters
Проблема рационализации и чрезмерного полагания на инструменты XAI: анализ объяснений больших языковых моделей
Suvorova A., В кн.: XXII национальная конференция по искусственному интеллекту с международным участием (КИИ-2025)Т. 1.: СПб.: Санкт-Петербургский Федеральный исследовательский центр РАН, 2025. С. 310–318.
В работе исследуется проблема чрезмерного полагания (overreliance) пользователей на результаты интерпретации моделей машинного обучения, а также способов ее решения с помощью пояснений, генерируемых большими языковыми моделями (LLM). Результаты эксперимента показали, что большинство моделей, так же как и пользователи-люди в исходном эксперименте, игнорировали аномалии или предлагали правдоподобные, но ложные объяснения, рационализируя выводы. Это указывает на риски ...
Added: February 15, 2026
Language: Russian
Text on another site
Keywords: инженерия знаниймоделирование рассужденийБольшие языковые модели (LLMs)
XXII национальная конференция по искусственному интеллекту с международным участием (КИИ-2025)
Similar publications
Proceedings of the 4th Workshop on NLP for Music and Audio (NLP4MusA 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
Generating and Debugging Java Code using LLMs based on Associative Recurrent Memory
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
Искусственный интеллект как симулякр смысла
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
SIGNAL: Dataset for Semantic and Inferred Grammar Neurological Analysis of Language
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
MADD: Multi-Agent Drug Discovery Orchestra
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
3MDBench: Medical Multimodal Multi-agent Dialogue Benchmark
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
Transformers and State-Space Models: Fine-Tuning Techniques for Solving Differential Equations
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
Application of Large Language Models to Solving Differential Equations: Constructing Baseline Models with LSTM and GRU
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
О разработке подхода к автоматизированному сбору и интеллектуальной обработке данных с применением методов веб-скрейпинга и больших языковых моделей (на примере задачи по извлечению оценок уровней готовности технологий)
Grozovskiy F., Loginova I., Научно-техническая информация. Серия 2: Информационные процессы и системы 2025 № 8 С. 27–36
Предлагается подход к автоматизированному извлечению и структурированию информации из текста, сочетающий веб-скрейпинг для сбора данных из онлайн-источников и большую языковую модель для их последующей интеллектуальной обработки. В качестве объекта исследования выбраны тексты новостных публикаций об уровнях готовности технологий с сайта CNews для апробации разработанной методики в рамках конкретной предметной области. Точность выделения моделью оценок технологической ...
Added: August 11, 2025
Вперед к истокам: обзор подходов к изучению политических предубеждений больших языковых моделей
Muronets V., Политическая наука 2025 № 2 С. 204–226
Political bias of Large Language Models has frequently become a topic for scientific investigation. Most of the researchers tend to compete in inventing more original ways of identifying bias rather than posing new research questions related to it besides “Is this model politically biased?” and “What is the character of its bias?”. To properly evaluate ...
Added: May 30, 2025
Исследование прикладного использования языковых моделей на основе метода генерации с дополненной выборкой
Loginova I., Grozovskiy F., Искусственный интеллект и принятие решений 2025 № 2 С. 73–89
The article presents a qualitative analysis of Russian and global cases of development and implementation of Retrieval-Augmented Generation models (RAG models) to address applied analytical and business tasks. RAG models outperform traditional large language models in accuracy, relevance, and contextual appropriateness of generated responses by utilizing external knowledge sources. This makes Retrieval-Augmented Generation an important ...
Added: May 20, 2025
Подход к созданию сервиса генерации программного кода мобильных приложений с использованием больших языковых моделей
Резуник Л., Александров Д.В., ИТ-Стандарт 2024 № 4 С. 34–41
Machine learning technologies and various tools for code generation have had a significant impact on the field of software development in recent years. Although most of the existing solutions are not built exactly for code generation, programmers apply them in different tasks. Not many of the existing AI solutions work well with less common languages, ...
Added: December 30, 2024
Using large language models for extracting and pre-annotating texts on mental health from noisy data in a low-resource language
Sergei Koltcov, Surkov A., Koltsova O. et al., PeerJ Computer Science, США 2024 Vol. 10 Article e2395
Recent advancements in large language models (LLMs) have opened new possibilities for developing conversational agents (CAs) in various subfields of mental healthcare. However, this progress is hindered by limited access to high-quality training data, often due to privacy concerns and high annotation costs for low-resource languages. A potential solution is to create human-AI annotation systems ...
Added: December 2, 2024
ПРИМЕНЕНИЕ СТИЛОМЕТРИИ ДЛЯ ОПРЕДЕЛЕНИЯ СГЕНЕРИРОВАННЫХ ТЕКСТОВ
Е. А. Сальников, А. А. Бонч-Осмоловская, В кн.: Информационные технологии в гуманитарных исследованиях: Материалы Международной научно-практической конференции, Красноярск, 25–28 сентября 2023 г.: Сибирский федеральный университет, 2023. С. 176–182.
В рамках данного доклад будет проанализировано использование стилометрической метрики дельта Бёрроуза в качестве метода для определения искусственного (т. е. сгенерированного языковой моделью) текста. Данными для эксперимента послужили дневники – как дневниковые записи случайно выбранных авторов, так и дневниковые записи М. М. Пришвина. В качестве данных языковых моделей послужили дневниковые записи, сгенерированные при помощи языковых моделей ...
Added: October 11, 2024
ТЕХНОЛОГИИ РАЗРАБОТКИ ИНСТРУМЕНТАЛЬНЫХ СРЕДСТВ (ТРИС-2023): материалы конференции
Таганрог: Издательство ЮФУ, 2023.
УДК 001.891:004.9 ТЕХНОЛОГИИ РАЗРАБОТКИ ИНСТРУМЕНТАЛЬНЫХ СРЕДСТВ ТРИС-2023: материалы конференции.− Таганрог: Издательство ЮФУ, 2023. − 191 с. ...
Added: December 16, 2023
Двадцать первая Национальная конференция по искусственному интеллекту с международным участием, КИИ-2023
Смоленск: Принт-Экспресс, 2023.
The first volume contains the plenary reports and reports of the conference participants presented in the following sections: Section 1 "Knowledge Engineering" Section 2 "Data Mining" Section 3 "Intelligent agents, robots, intelligent control, computer vision" Section 4 "Machine learning, neural network methods" ...
Added: October 30, 2023
Intelligent Decision Technologies: Proceedings of the 13th KES-IDT 2021 Conference
Сингапур: Springer, 2021.
This book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14–16, 2021.  The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discussion about them under the common title "Intelligent Decision Technologies". The conference has been creating for years a platform for knowledge ...
Added: August 1, 2021
ТЕХНОЛОГИИ РАЗРАБОТКИ ИНФОРМАЦИОННЫХ СИСТЕМ (ТРИС-2017): Материалы VIII Международной научно-технической конференции
Ростов н/Д: Южный федеральный университет, 2017.
ТЕХНОЛОГИИ РАЗРАБОТКИ ИНФОРМАЦИОННЫХ СИСТЕМ (ТРИС-2017): материалы конференции.− Таганрог: Издательство ЮФУ, 2017. − 239 с. Работа печатается в рамках гранта РФФИ № 17-07-20324 Г ...
Added: December 14, 2017
Инженерия знаний основа создания экспертных систем
Grachev N. N., В кн.: Инновации на основе информационных и коммуникационных технологий: Материалы международной научно-практической конференции, 2014.: М.: НИУ ВШЭ, 2014. С. 62–64.
Статья посвящена вопросам методологии обучения человека как обучающейся системе. Значительное место отводится анализу приобретения знаний как основной задачи инженерии знаний и ее развитии в создании экспертных систем ...
Added: December 9, 2014
Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD - 2010)
SciTePress, 2010.
"Knowledge Engineering and Ontology Development - 2010" (KEOD - 2010) Conference Proceeings ...
Added: November 15, 2014
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