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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
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Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers

Vol. 12602. Springer, 2021.
Under the general editorship: W. . van der Aalst, V. Batagelj, Ignatov D. I., M. Khachay, Koltsova O., A. Kutuzov, Sergei O. Kuznetsov, Lomazova I. A., N. Loukachevitch, A. Napoli, A. Panchenko, Pardalos P. M., M. Pelillo, Savchenko A., E. Tutubalina
Chapters
Do topics make a metaphor? Topic modeling for metaphor identification and analysis in Russian.
Badryzlova Y., Nikiforova A., Lyashevskaya O., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 69–81.
The paper examines the efficiency of topic models as features for computational identification and conceptual analysis of linguistic metaphor on Russian data. We train topic models using three algorithms (LDA and ARTM – sparse and dense) and evaluate their quality. We compute topic vectors for sentences of a metaphor-annotated Russian corpus and train several classifiers ...
Added: October 7, 2020
Checking Conformance between Colored Petri Nets and Event Logs
Carrasquel Gamez J. C., Mecheraoui K., Lomazova I. A., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 435–452.
Event logs of information systems consist of recorded traces, describing executed activities and involved resources (e.g., users, data objects). Conformance checking is a family of process mining techniques that leverage such logs to detect whether observed traces deviate w.r.t some specification model (e.g., a Petri net). In this paper, we present a conformance checking method ...
Added: October 20, 2020
DaNetQA: a yes/no Question Answering Dataset for the Russian Language
Glushkova T., Machnev A., Fenogenova A. et al., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 57–68.
Added: November 22, 2020
Data and Reference Semantic-Based Simulator of DB-nets with the Use of Renew Tool
Rigin A., Shershakov Sergey, , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 453–465.
Complexity of software systems is constantly growing, which is even more aggravated by concurrency of processes in systems, so modeling and validating such systems is necessary for detecting and eliminating failures. One of the most well-known formalisms for solving this problem is Petri nets and their extensions such as colored Petri nets, reference nets, and ...
Added: November 26, 2020
Semi-automatic Manga Colorization Using Conditional Adversarial Networks
Maksim Golyadkin, Makarov I., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 230–242.
Manga colorization is time-consuming and hard to automate. In this paper, we propose a conditional adversarial deep learning approach for semi-automatic manga images colorization. The system directly maps a tuple of grayscale manga page image and sparse color hint constructed by the user to an output colorization. High-quality colorization can be obtained in a fully ...
Added: April 9, 2021
Automated Image and Video Quality Assessment for Computational Video Editing
Konstantin Lomotin, Makarov I., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 243–256.
We study non-reference image and video quality assessment methods, which are of great importance for computational video editing. The object of our work is image quality assessment (IQA) applicable for fast and robust frame-by-frame multipurpose video quality assessment (VQA) for short videos. We present a complex framework for assessing the quality of images and videos. The ...
Added: April 9, 2021
Community Detection Based on the Nodes Role in a Network: The Telegram Platform Case
Tikhomirova K., Makarov I., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 294–302.
The paper studies the community detection problem on Telegram channels. The dataset is received from TGStat service and includes the information of 58k forwards between 100 politician Telegram channels. We implement modern clustering approaches to solve the problem of missing social links. Our study is based on a combination of structural features with strategy-based attributes, ...
Added: April 9, 2021
Human Action Recognition for Boxing Training Simulator
Anton Broilovskiy, Makarov I., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 331–343.
Computer vision technologies are widely used in sports to control the quality of training. However, there are only a few approaches to recognizing the punches of a person engaged in boxing training. All existing approaches have used manual feature selection and trained on insufficient datasets. We introduce a new approach for recognizing actions in an ...
Added: April 9, 2021
Generating Sport Summaries: A Case Study for Russian
Malykh V., Porplenko D., Tutubalina E., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 149–161.
We present a novel dataset of sports broadcasts with 8,781 games. The dataset contains 700 thousand comments and 93 thousand related news documents in Russian. We run an extensive series of experiments of modern extractive and abstractive approaches. The results demonstrate that BERT-based models show modest performance, reaching up to 0.26 ROUGE-1F-measure. In addition, human evaluation ...
Added: May 10, 2021
Linking Friends in Social Networks using HashTag Attributes
Gerasimova O., Syomochkina V., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 269–281.
Social networks are an integral part of modern life. They allow us to communicate online and exchange all kinds of information. In this paper, we consider the social network Instagram and its hashtags as a key tool for finding relevant information and new friends. The aim of our work is an empirical analysis of hashtags for posts in ...
Added: June 7, 2021
ELMo and BERT in Semantic Change Detection for Russian
Rodina Y., Трофимова Ю. Е., Kutuzov A. B. et al., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 175–186.
We study the effectiveness of contextualized embeddings for the task of diachronic semantic change detection for Russian language data. Evaluation test sets consist of Russian nouns and adjectives annotated based on their occurrences in texts created in pre-Soviet, Soviet and post-Soviet time periods. ELMo and BERT architectures are compared on the task of ranking Russian ...
Added: October 4, 2021
BERT for Sequence-to-Sequence Multi-label Text Classification.
Yarullin R., Serdyukov P., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 187–198.
Added: October 4, 2021
Study of Strategies for Disseminating Information in Social Networks Using Simulation Tools
Usanin A., Zimin I., Elena Zamyatina, , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 303–315.
The paper presents simulation tools for investigation not only the structural characteristics of social networks in order to study information dissem-ination strategies, but also the dynamic characteristics of this process. A feature of this software system is not only the ability to work with virtual social networks, but also with data from real networks. To ...
Added: October 30, 2021
RST Discourse Parser for Russian: An Experimental Study of Deep Learning Models
Chistova E., Shelmanov A., Pisarevskaya D. et al., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 105–119.
This work presents the first fully-fledged discourse parser for Russian based on the Rhetorical Structure Theory of Mann and Thompson (1988). For the segmentation, discourse tree construction, and discourse relation classification we employ deep learning models. With the help of multiple word embedding techniques, the new state of the art for discourse segmentation of Russian texts is achieved. We found ...
Added: November 17, 2021
Research target: Computer Science
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: AISTАИСТ
Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers
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