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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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AGGILE: Automated Graph Generation for Inference and Language Exploration

CEUR Workshop Proceedings. 2025. Vol. 3977.
Фирсанова В. И., Хлусова Я. К., Khlusova Y., Khlusova Y.
Language: English
Keywords: knowledge graphsexplainable AI (XAI)large language models (LLMs)Automated Graph Generation
Similar publications
Joint Proceedings of the ESWC 2025 Workshops and Tutorials co-located with 22nd Extended Semantic Web Conference (ESWC 2025), Portorož, Slovenia, June 1-2, 2025
Фирсанова В. И., Хлусова Я. К., CEUR Workshop Proceedings, 2025.
Knowledge graphs are widely used in Retrieval Augmented Generation (RAG) and Explainable AI (XAI), since they can illustrate semantic relationships generated by Large Language Models (LLMs). Recent studies focus on generating knowledge graphs from unstructured data to improve RAG performance; however, they do not explain the underlying graph structure. The analysis of synthetic graphs behind ...
Added: August 4, 2026
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
Challenges and Risks to the Inclusion of AI for Environmental Applications
Aleksandrova I., Milshina Y., , in: Artificial Intelligence Enabled Real Time Environmental Monitoring.: Springer, 2026. Ch. 10 P. 199–229.
Artificial intelligence is increasingly becoming a valuable tool in environmental science, providing significant benefits in the processing of high-volume datasets, improving predictive models, and better enabling the efficient monitoring of ecosystems. Its ability to identify patterns, automate tedious tasks, and facilitate data-driven decision-making makes it of extreme value in tackling climate change, biodiversity loss, and ...
Added: January 19, 2026
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
26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED
Springer, 2025.
This three-volume set CCIS 2590-2592 constitutes poster papers and late breaking results, workshops and tutorials, practitioners, industry and policy track, doctoral consortium, blue sky and wideAIED papers presented at the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22–26, 2025.   The 72 full papers and 73 short papers (72 ...
Added: September 4, 2025
Developing an Approach for Automated Data Collection and Mining Using Web Scraping Techniques and Large Language Models: A Case Study on Extracting Technology Readiness Level Assessments
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The paper proposes an approach to the automated extraction and structuring of information from text, combining web scraping for data collection from online sources with a large language model for subsequent data mining. As a case study, texts from news publications on technology readiness levels from the CNews website were chosen to test the developed methodology in a ...
Added: August 25, 2025
Knowledge Graph Completion with Mixed Geometry Tensor Factorization
Yusupov V., Rakhuba M., Frolov E., , in: Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, 3-5 May 2025, Splash Beach Resort in Mai Khao, Thailand, PMLR: vol. 258Vol. 258.: PMLR, 2025. P. 4924–4932.
Added: May 25, 2025
Fast gradient-free activation maximization for neurons in spiking neural networks
Pospelov N., Chertkov A., Beketov M. et al., Neurocomputing 2025 Vol. 618 Article 129070
Elements of neural networks, both biological and artificial, can be described by their selectivity for specific cognitive features. Understanding these features is important for understanding the inner workings of neural networks. For a living system, such as a neuron, whose response to a stimulus is unknown and not differentiable, the only way to reveal these ...
Added: December 14, 2024
Synthesis of multilevel knowledge graphs: Methods and technologies for dynamic networks
Man T., Vodyaho A., Ignatov D. I. et al., Engineering Applications of Artificial Intelligence 2023 Vol. 123 Article 106244
Knowledge Graphs is one of the most popular techniques for knowledge-based modelling in various subdomains of modern AI technologies ranging from natural language processing to e-commerce recommendations and cyberphysical systems. Even complex technical systems like telecommunication networks could be modelled by means of Knowledge Graphs. However, there are serious challenges when we deal with such ...
Added: November 23, 2023
Analyzing COVID-19 Medical Papers Using Artificial Intelligence: Insights for Researchers and Medical Professionals
Dmitry Soshnikov, Petrova T., Soshnikova V. et al., Big Data and Cognitive Computing 2022 Vol. 6 No. 1 Article 4
Since the beginning of the COVID-19 pandemic almost two years ago, there have been more than 700,000 scientific papers published on the subject. An individual researcher cannot possibly get acquainted with such a huge text corpus and, therefore, some help from artificial intelligence (AI) is highly needed. We propose the AI-based tool to help researchers ...
Added: February 22, 2022
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Nowadays, due to the growing demand for interdisciplinary research and innovation, different scientific communities pay substantial attention to cross-domain collaboration. However, having only information retrieval technologies in hands might be not enough to find prospective collaborators due to the large volume of stored bibliographic records in scholarly databases and unawareness about emerging cross-disciplinary trends. To ...
Added: January 14, 2021
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