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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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Matchings with Interval Order Preferences: Efficiency vs Strategy-proofness

Procedia Computer Science. 2014. Vol. 31. P. 807–813.
Sofya Kiselgof

We investigate models of two-sided matching markets without transfers. Examples of such markets include marriage market, universities-applicants market and others. Gale and Shapley in 1962 first introduced this kind of problems in the literature. They considered one-to-one and one-to-many markets, where preferences of individuals on the one side over individuals on the other side were strict.

In this paper we analyze a modification of the classical Gale-Shapley admission problem, where preferences of universities are considered to be interval orders. Interval order allows a specific form of indifference in the preference relation. Imagine, each alternative is described with an interval [l, u], and one alternative dominates another if and only if intervals do not overlap and lower bound of the first interval is greater than upper bound of the second interval. Preferences with such property may occur in the cases, when applicants’ scoring system (interview, exam or sum of points) is not exactly accurate.

In the previous paper we have shown the existence of a stable matching and provided the criteria of applicant Pareto-optimality of a stable matching, based on Stable Improvement Cycles.

However, the Pareto-efficient stable mechanism is not (in general) strategy-proof for applicants. We provide a strategy-proof applicant-proposing deferred acceptance with tie-breaking, where tie-breaking procedure is organized in a special way. This special tie-breaking allows to lower chances of an applicant-inefficient stable matching (in comparison to that with random-tie breaking).

Research target: Mathematics Economics and Management Computer Science
Priority areas: economics IT and mathematics
Language: English
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DOI
Text on another site
Keywords: matchingsPareto optimalityinterval ordersstable matchings
Publication based on the results of:
Theoretical and numerical study of advanced mathematical models in the social, economic, political and financial fields (2014)
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