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Subject
News
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
Researchers Develop Method for Direct Generation of Regulatory DNA
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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?

ERP Correlates of the Semantic Violations in the Deepfakes Containing Disinformation Regarding COVID-19: Pilot Study

P. 120–123.
Monahhova E., Morozova A., Gorodnicheva Y., Zinchenko O., Moiseeva V., Klucharev V.

The current study examined behavioral and electrophysiological responses to attitude-consistent and attitude-inconsistent auditory deepfakes on COVID-19 vaccination topic. Deepfakes portrayed Russian media- influencers (two speaker types: a prominent medical doctor and COVID-dissident), broadcasting statements opposite to their public opinion. We hypothesized that people would evaluate the trust-associated statements higher to deepfake aligning with their internal attitudes. We employed electroencephalography (EEG) to record participants' brain responses, expecting the N400-like amplitude to be more negative when hearing a manipulated audio recording (deepfake) mismatching their internal attitudes and the speaker's public opinion on the topic. Overall, 29 participants performed a pilot study: they listened to deepfakes, rated their level of agreement to trust-related statements for each recording and completed questionnaires on analytical thinking, need for cognition and tendency to conform to others. The behavioral results suggested that trust-related statements were affected by need for cognition score and speaker type. As for the EEG results, the pro-vaccination group demonstrated a delayed N400-like response to the COVID- dissident's statements mismatching her public opinion, while anti-vaccination group demonstrated a similar N400-like response to the medical doctor's deepfakes statements mismatching his public opinion, reflecting unexpected, but attitude-supportive information.

Language: English
DOI
Keywords: искусственный интеллектдовериевосприятие event-related potentialsdisinformationдезинформация ЭЭГдипфейкdeepfakeEEG (electroencephalography) artificial intelligenceВП (вызванные потенциалы)

In book

2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN)
IEEE, 2024.
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