Teaching a Machine to Read the Past: HSE Develops Neural Network to Decipher Manuscripts
Diaries and letters are an invaluable resource for humanities scholars. But what can be done when the text is impossible to read? At the HSE Faculty of Humanities, this challenge has been translated into the language of mathematics: a team of philologists, historians, and machine learning specialists has created an information system that not only recognises illegible handwriting but also helps analyse archival content.
How Neural Networks Detect and Interpret Wordplay: New Insights from HSE Researchers
An international team including researchers from the HSE Faculty of Computer Science has presented KoWit-24, an annotated dataset of 2,700 Russian-language Kommersant news headlines containing wordplay. The dataset enables an assessment of how artificial intelligence detects and interprets wordplay. Experiments with five large language models show that even advanced systems still make mistakes, and that interpreting wordplay is more challenging for them than detecting it. The results were presented at the RANLP conference; the paper is available on Arxiv.org, and the dataset and the code for reproducing the experiments are available on GitHub.
Educational Programmes on Robotics and Neural Network Technologies Launch at HSE University’s Faculty of Computer Science
Every year, in response to IT industry demands, the Higher School of Economics Faculty of Computer Science launches new educational programmes while updating existing ones. In 2026, the faculty introduced Bachelor’s and Master’s degree programmes in robotics for the first time.
Group and Shuffle: Researchers at HSE University and AIRI Accelerate Neural Network Fine-Tuning
Researchers at HSE University and the AIRI Institute have proposed a method for quickly fine-tuning neural networks. Their approach involves processing data in groups and then optimally shuffling these groups to improve their interactions. The method outperforms alternatives in image generation and analysis, as well as in fine-tuning text models, all while requiring less memory and training time. The results have been presented at the NeurIPS 2024 Conference.
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‘When You Have a Lot to Do, You Find Time for Everything’
Egor Churaev specialises in neural networks. In an interview for the HSE Young Scientists project, he talked about his program for determining the emotions and engagement of online conference participants, his trip to Brazil, and his sports hobbies.
Beauty in Details: HSE University and AIRI Scientists Develop a Method for High-Quality Image Editing
Researchers from theHSE AI Research Centre, AIRI, and the University of Bremen have developed a new image editing method based on deep learning—StyleFeatureEditor. This tool allows for precise reproduction of even the smallest details in an image while preserving them during the editing process. With its help, users can easily change hair colour or facial expressions without sacrificing image quality. The results of this three-party collaboration were published at the highly-cited computer vision conference CVPR 2024.
HSE University at VK Fest: VR Games and Emotion Recognition
On July 13-14, 2024, the annual large-scale VKontakte festival took place at Moscow’s Luzhniki Stadium. HSE University, as usual, participated in the event. The university's tent featured a variety of activities, including emotion recognition challenge, quizzes about artificial intelligence, IT career testing, a smile detector, VR gaming, and a blue tractor equipped with a smart sprinkler system.
Russian Researchers Improve Neural Networks' Spatial Navigation Performance
Researchers at HSE University, MISiS National University of Science and Technology, and the Artificial Intelligence Research Institute (AIRI) have developed an enhanced approach to reinforcement learning for neural networks tasked with navigation in three-dimensional environments. By using the attention mechanism, they managed to improve the performance of a graph neural network by 15%. The study results have been published in IEEE Access.
Neural Network Developed at HSE Campus in Perm Will Determine Root Cause of Stroke in Patients
Specialists at HSE Campus in Perm and clinicians at Perm City Clinical Hospital No. 4, have been collaborating to develop a neural network capable of determining the root cause of a stroke. This marks the world's first attempt to create such a system, the developers note.
HSE Researchers Teach Neural Networks to Better Detect Humour
A group of scientists from the HSE Faculty of Computer Science has conducted a study on the ability of neural networks to detect humour. It turns out that for more reliable recognition, it’s necessary to change the approach to creating datasets on which neural networks are trained. The scientists presented these results at one of the world's most important conferences on natural language processing — EMNLP 2023.
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