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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Диалоговая система для сопровождения человека, страдающего реактивной депрессией. Лингвистический аспект

Глобальный научный потенциал. 2024. Т. 155. № 2. С. 226–231.
Сиверцев Е. Ю., Фирсанова В. И.

The purpose of the article is to give recommendations for creating a dialogue system that can be connected to any electronic device (personal computer, smartphone) and should always be at the disposal of a person suffering from reactive depression. The method of distributive semantics is used: searching for the meaning of a word by its surroundings. The result of applying this method is the opportunity provided by computational linguistics to combine an almost unlimited amount of material extracted from the Internet with the ability of modern artificial intelligence to self-learn. The user is in constant communication with a personalized dialogue agent, which is constantly being improved by expanding the knowledge base about the individual characteristics of a person’s character and fine-tuning the neural network algorithm for natural language processing based on this data.

Research target: Philology and Linguistics
Language: Russian
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Keywords: искусственный интеллектпользовательдепрессиядистрибутивная семантикаdepressionдиалоговая системаdistributive semanticsdialogue systems artificial intelligenceself-learning systemuserсамообучающая система
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