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pro vyhledávání: '"Anton Frolov"'
Currently, dialogue systems have achieved high performance in processing text-based communication. However, they have not yet effectively incorporated visual information, which poses a significant challenge. Furthermore, existing models that incorpor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c46027af7179ff747adc70f1f853cc25
Autor:
Anton Frolov
Publikováno v:
2021 International Conference on Information Technology and Nanotechnology (ITNT).
Autor:
Andre Kunert, Sandro Weber, Adrian Kreskowski, Tim Weissker, Stephan Beck, Carl Matthes, Bernd Froehlich, Emmanouil Angelidis, Alexander Kulik, Anton Frolov
Publikováno v:
VR
2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)
2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)
We present the collaborative Virtual Reality Neurorobotics Lab, which allows multiple collocated and remote users to experience, discuss and participate in neurorobotic experiments in immersive virtual reality. We describe the coupling of the Neuroro
Publikováno v:
CoNLL
Marcheggiani, D, Frolov, A & Titov, I 2017, A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling . in Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017) . pp. 411–420, 21st Conference on Computational Natural Language Learning, Vancouver, Canada, 3/08/17 . https://doi.org/10.18653/v1/K17-1041
Marcheggiani, D, Frolov, A & Titov, I 2017, A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling . in Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017) . pp. 411–420, 21st Conference on Computational Natural Language Learning, Vancouver, Canada, 3/08/17 . https://doi.org/10.18653/v1/K17-1041
We introduce a simple and accurate neural model for dependency-based semantic role labeling. Our model predicts predicate-argument dependencies relying on states of a bidirectional LSTM encoder. The semantic role labeler achieves competitive performa
Publikováno v:
ACM SIGARCH Computer Architecture News. 41:53-58
Processing large volumes of information in real time requires large amounts of computational power, which consumes a significant amount of energy. With the rise in the amount of data produced, energy-efficient high-performance information processing
Publikováno v:
WMT
This paper describes Yandex School of Data Analysis (YSDA) submission for WMT2016 Shared Task on Quality Estimation (QE) / Task 1: Sentence-level prediction of post-editing effort. We solve the problem of quality estimation by using a machine learnin
Autor:
Alexei Apisarov, A. A. Red’kin, Alexander Gusev, Alexander Dedyukhin, Anton Frolov, Olga Tkacheva, Yurii Zaikov
Publikováno v:
ECS Transactions. 16:317-324
The electrical conductivity of low temperature electrolytes for aluminum electrolysis has been measured. The potassium cryolite was the basic melt. Additions of LiF and NaF increased the conductivity of (KF +AlF3) molten mixtures but Al2O3 decreased
Publikováno v:
CIKM
With the rise in the amount information of being streamed across networks, there is a growing demand to vet the quality, type and content itself for various purposes such as spam, security and search. In this paper, we develop an energy-efficient hig
Autor:
Alexander Dedyukhin, Alexei Apisarov, Olga Tkacheva, Alexander A. Redkin, Yurii Zaikov, Anton Frolov, Alexander Gusev
Publikováno v:
ECS Meeting Abstracts. :3003-3003
not Available.