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June 11, 2026
Doctoral Student at HSE University Reveals Hidden Layout of Ancient Parion
İdil Malgil, a researcher at HSE University, conducted a UAV-based LiDAR survey of the ancient Roman city of Parion in present-day Turkey. The high density of the scans allowed the team to detect subtle terrain features concealed beneath the ground and vegetation. The survey revealed traces of entire neighbourhoods, terraced structures, and walls that had remained invisible during routine excavations and could not be identified through aerial photography. The findings have been published in Ancient Civilizations from Scythia to Siberia.
June 11, 2026
Mathematicians from Nizhny Novgorod and Shanghai Study System Stability
Mathematicians at HSE University–Nizhny Novgorod, in collaboration with colleagues from Tongji University in Shanghai, are investigating the fundamental causes of structural stability in systems and the mechanisms underlying its disruption. In this interview with the HSE News Service, Prof. Olga Pochinka, Head of the International Laboratory of Dynamical Systems and Applications at HSE University–Nizhny Novgorod and leader of the project ‘Qualitative Theory of Systems of Ordinary and Partial Differential Equations,’ discusses the project, which is being implemented as part of HSE University's International Academic Cooperation programme.
June 11, 2026
Neurolinguists Assist in Awake Surgery on 11-Year-Old Patient with Epilepsy
Researchers at the HSE Centre for Language and Brain took part in a rare awake neurosurgical procedure performed on an 11-year-old patient with drug-resistant epilepsy. Working alongside surgeons at the Voyno-Yasenetsky Centre of Specialised Medical Care for Children in Solntsevo, they monitored the resection of a portion of the left temporal lobe, where the epileptic focus had been identified.

 

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SumTitles: a Summarization Dataset with Low Extractiveness

Ch. 503. P. 5718–5730.
Malykh V., Chernis K., Artemova E., Piontkovskaya I.

The existing dialogue summarization corpora are significantly extractive. We introduce a methodology for dataset extractiveness evaluation and present a new low-extractive corpus of movie dialogues for abstractive text summarization along with baseline evaluation. The corpus contains 153k dialogues and consists of three parts: 1) automatically aligned subtitles, 2) automatically aligned scenes from scripts, and 3) manually aligned scenes from scripts. We also present an alignment algorithm which we use to construct the corpus.

Language: English
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Keywords: dialog applicationLanguage modelstext summarisation
Publication based on the results of:
Development of Mathematical Models and Methods for Recommender Systems and Natural Language Processing (2020)

In book

Proceedings of the 28th International Conference on Computational Linguistics
International Committee on Computational Linguistics, 2020.
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