• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Articles
  • AGGILE: Automated Graph Generation for Inference and Language Exploration
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

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
F. M. Grozovskiy, I. V. Loginova, Automatic Documentation and Mathematical Linguistics 2025 Vol. 59 No. 4 P. 269–278
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
Cross-Domain Co-Author Recommendation Based on Knowledge Graph Clustering
Ahmed Munna M. T., Delhibabu R., , in: Intelligent Information and Database Systems: 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7–10, 2021, Proceedings.: Springer, 2021. P. 782–795.
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
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit