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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics

Vol. 2: Short papers. Wien : Association for Computational Linguistics, 2025.
Academic editor: W. Che, J. Nabende, E. Shutova, P. Mohammad Taher
Chapters
Automatic detection of dyslexia based on eye movements during reading in Russian
Laurinavichyute A., Lopukhina A., Reich D., , in: Proceedings of the 63rd Annual Meeting of the Association for Computational LinguisticsVol. 2: Short papers.: Wien: Association for Computational Linguistics, 2025. P. 59–66.
Dyslexia, a common learning disability, requires an early diagnosis. However, current screening tests are very time- and resourceconsuming. We present an LSTM that aims to automatically classify dyslexia based on eye movements recorded during natural reading combined with basic demographic information and linguistic features. The proposed model reaches an AUC of 0.93 and outperforms the ...
Added: January 19, 2026
Language: English
DOI
Text on another site
Keywords: machine learningcomputational linguisticscomputer linguistics natural language processing
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics
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Automatic Classification vs. Human Annotation of Emotions in Everyday Spoken Russian: A Case Study of the ESC Corpus
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This paper presents the results of an experiment comparing automatic and human emotion and sentiment detection in transcripts of Russian spontaneous speech. The study is based on a dataset derived from the Everyday Student Conversations corpus of Russian speech (ESC Corpus/KURS), comprising 26,137 speaker turns (326,527 tokens) obtained through automatic speech recognition of 226 macro-episodes ...
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Автоматизированное формирование журналов событий на основе неструктурированных Интернет-источников для задач анализа процессов
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Scalable machine learning approach to disordered s-wave superconductors
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Proceedings of the 9th Student Research Workshop associated with the International Conference Recent Advances in Natural Language Processing
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Added: March 17, 2026
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Added: February 28, 2026
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