Tag "neural networks"

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.

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.

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.

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.