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News
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Balancing Equity, Efficiency, and Stability: Designing Permit Trading Schemes for Sustainable Climate Cooperation

Journal of Environmental Economics and Management. 2025.
Bakalova I., Eyckmans J.

This paper demonstrates how emission permit trading systems, with strategically designed initial allocations, can simultaneously balance the competing goals of economic efficiency, distributional equity, and coalition stability. We develop a novel theoretical framework that embeds participation constraints into the welfare optimization problem, ensuring countries voluntarily join a coalition. Using numerical simulation results of a RICE type of integrated assessment model, including climate-induced capital depreciation and total factor productivity growth losses, we determine welfare maximizing initial allocations of permits that address participation constraints and equity concerns.
Our findings demonstrate that carefully designed permit allocations can sustain stable international cooperation while preserving climate ambitions.  The welfare maximizing permit allocations exhibit a distinct temporal pattern directing permits earlier in time to vulnerable, low-income regions (notably Africa) and later to wealthier regions.

Research target: Economics and Management
Language: English
Full text
Keywords: equityinternational environmental agreementsintegrated assessment modelspermit tradinginitial permit allocations
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