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Use Case 5: LLM-driven creation of natural hazard geodatabase from digital mass media
P. 167–169.
In book
Geneva: International Telecommunication Union, 2025.
Severin N., Kartushov D., Urzhumov V. et al., , in: Advances in Information Retrieval: 48th European Conference on Information Retrieval, ECIR 2026, Delft, The Netherlands, March 29 – April 2, 2026, Proceedings, Part II. (LNCS, volume 16484).: Cham: Springer Publishing Company, 2026. P. 508–517.
Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in cap-turing rich user semantics beyond interaction patterns. Large Language Models (LLMs) present opportunities to enhance user understanding with their reasoning capabilities, yet existing integration approaches cre-ate prohibitive inference costs in real time. To address these limitations, we present a ...
Added: June 18, 2026
Stepin A., Mozikov M., Kabanov A. et al., IEEE Access 2026 Vol. 14 P. 48127–48144
The deployment of large language models (LLMs) in interactive roles such as automated negotiators, customer service agents, and strategic partners requires them to handle not only logical tasks but also the socio-emotional dimensions of interaction. In these situations, success often relies on understanding social cues, building trust, and using persuasion effectively. These skills are closely ...
Added: June 16, 2026
Abdullaeva I., Karpukhin I., Filatov A. et al., IEEE Access 2026 Vol. 14 P. 59390–59408
Event sequences, a specialized type of tabular data annotated with timestamps, are prevalent across practical domains such as finance, retail, social networks, and healthcare. Despite the importance of event sequence modeling and analysis, there has been little effort to adapt Large Language Models (LLMs) to this domain. In this paper, we propose a novel solution ...
Added: June 16, 2026
Omopekunola M., JOURNAL OF EDUCATIONAL TECHNOLOGY DEVELOPMENT AND EXCHANGE 2026 Vol. 19 No. 2 P. 141–165
Educational assessments, from low-stakes classroom tests to high-stakes national examinations, require item pools that are valid, fair, and secure. Automated Item Generation (AIG) aims to efficiently produce large pools of calibrated test items. This paper adopts a two-part design: (1) a brief historical mapping situating LLM-based AIG within the broader AIG trajectory; and (2) a ...
Added: June 9, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 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
Jin S., Panfilov P., Сулейкин А. С., Труды Института системного программирования РАН 2025 Т. 37 № 6 С. 163–176
In the modern restaurant business, accurate mapping of product nomenclatures between restaurants and suppliers is a critical task. Effective inventory management and procurement optimization directly impact business profitability. With the increase in suppliers and product variety, traditional mapping methods become less efficient. This study proposes using large language models (LLM) to automate and improve the ...
Added: April 17, 2026
Buzaev F., Пугачёва Д. В., Sukharev I. et al., Transactions of the Association for Computational Linguistics 2026 P. 51–57
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: April 7, 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
Moses Oluoke Omopekunola, Elena Yu. Kardanova, Journal of Science Education and Technology 2026
High-stakes assessment is crucial for evaluating student performance and making significant educational decisions. Traditionally, the development of test items for such examinations has relied on manual development by subject matter experts. However, Automated Item Generation (AIG) using Large Language Models (LLMs) has emerged as a promising alternative, though systematic research on their application in high-stakes ...
Added: January 16, 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
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
Koltsova O., Surkov A., Procedia Computer Science 2025 Vol. 258 P. 2382–2390
Chest X-ray pathology prediction play a very important role in early disease detection, enabling timely intervention and improving patient outcomes. Detection of ethnic conflict mentioning, discussion, or verbal participation therein in user-generated content is a socially important task, as such content has been proven related to ethnic clashes on the ground. Yet this task has not been ...
Added: November 28, 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
Voevodina E., Современная зарубежная психология 2025 Т. 14 № 3 С. 172–181
Context and relevance. Well-being research faces methodological limitations of conventional psychometric measures, criticized for poor ecological validity, limited information yield, and inadequate capture of multidimensional construct of well-being. Advanced natural language processing (NLP) technologies offer solutions to these constraints. Objective. To evaluate opportunities and challenges of transformer-based NLP for well-being research. Methods and materials. We conducted an analytical review of ...
Added: October 9, 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
Бадина С. В., Turchaninova A. S., Baburin V. L. et al., Regional Research of Russia 2024 Vol. 14 No. 3 P. 503–511
Added: June 30, 2025
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
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
Semenova E., Mikhail Komarov, , in: Sustainable Green Conversion. Selected Papers from ISPR2024, October 10-12, 2024 Budva-Montenegro, Volume 1Vol. 1,2.: Springer, 2025. Ch. 9 P. 125–144.
The article investigates the impact of large language models (LLMs), such as ChatGPT, on productivity within the digital product development industry. The research highlights the transformative role of LLMs in enhancing task completion speed, job satisfaction, and reducing fatigue, particularly for junior employees and less experienced professionals. Through a survey-based approach, the study identifies that ...
Added: May 6, 2025