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News
October 5, 2026
Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.
October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.

 

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FactRuEval 2016: Evaluation of Named Entity Recognition and Fact Extraction Systems for Russian

P. 688–705.
Starostin A. S., Bocharov V. V., Alexeeva S. V., Bodrova A. A., Chuchunkov A. S., Dzhumaev S. S., Efimenko I. V., Granovsky D. V., Khoroshevsky V. F., Krylova I. V., Nikolaeva M. A., Smurov I. M., Toldova S. Y.

In this paper, we describe the rules and results of the FactRuEval informa- tion extraction competition held in 2016 as part of the Dialogue Evaluation initiative in the run-up to Dialogue 2016. The systems were to extract in- formation from Russian texts and competed in two named entity extraction tracks and one fact extraction track. The paper describes the tasks set be- fore the participants and presents the scores achieved by the contending systems. Additionally, we dwell upon the scoring methods employed for evaluating the results of all the three tracks and provide some preliminary analysis of the state of the art in Information Extraction for Russian texts. We also provide a detailed description of the composition and general orga- nization of the annotated corpus created for the competition by volunteers using the OpenCorpora.org platform. The corpus is publicly available and is expected to evolve in the future. 

Language: English
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Keywords: evaluationinformation extractionrelation extractionnamed entity recognitionfact extraction

In book

Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва,1–4 июля 2016 г.)
Вып. 15. , М.: Изд-во РГГУ, 2016.
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