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Incremental Topic Modeling for Scientific Trend Topics Extraction

2023Conference paperNikolai Gerasimenko, Alexander Chernyavskiy, Maria Nikiforova, Anastasia Ianina +1

Computational Linguistics and Intellectual Technologies

Rapid growth of scientific publications and intensive emergence of new directions and approaches poses a challenge to the scientific community to identify trends in a timely and automatic manner. We denote trend as a semantically homogeneous theme that is characterized by a lexical kernel steadily evolving in time and a sharp, often exponential, increase in the number of publications. In this paper, we investigate recent topic modeling approaches to accurately extract trending topics at an early stage. In particular, we customize the standard ARTM-based approach and propose a novel incremental training technique which helps the model to operate on data in real-time. We further create the Artificial Intelligence Trends Dataset (AITD) that contains a collection of early-stage articles and a set of key collocations for each trend. The conducted experiments demonstrate that the suggested ARTM-based approach outperforms the classic PLSA, LDA models and a neural approach based on BERT representations. Our models and dataset are open for research purposes.
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Verification of communicative types in the judicial public space of media discourse in the USA, Kazakhstan and Russia as a psycholinguistic marker of fact-checking

2023Journal articleGulzat T. Kussepova, Irina S. Karabulatova, Karlygash S. Kenzhigozhina, Aleksey O. Bakhus +1

Revista Amazonia Investiga

Modern psycholinguistic research and fact-checking actively explore the space of media discourse. However, the representation of the judicial space in the mass media has not been sufficiently studied due to the peculiarities of communicative behavior in the judicial and legal space of the ethno-socius and the attitude to the judiciary. The authors hypothesize that the differences in public behavior in court and the coverage of the work of courts in the American, Kazakh and Russian media are due to the socio-cultural features of the phenomena of judicial and legal communication in public space under the influence of established traditions in such coordinate systems as “person – judicial system”, “openness – closeness of society”, “unity – disunity of society”, “accessibility – stigmatization”, “court – journalistic investigation”, etc. The results confirm the hypothesis of the authors' team, revealing the difference in the perception of the judicial system in the USA, Kazakhstan and Russia, illustrating the "rejection" of the Soviet and post-Soviet stigmatization of the judicial and legal space by the Kazakh society towards democratic norms. The prospects of the study are related to the subsequent development of an automatic system for evaluating speech behavior strategies in court and their coverage in the media as a category of fact-checking.
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Сложная система наведения для открытого воздушного канала передачи высокостабильной оптической частоты

2023Conference talkAlexey Legoshin, Ксения Лискова, K. S. Kudeyarov, G. A. Vishnyakova

Труды 65-й Всероссийской научной конференции МФТИ в честь 115-летия Л.Д.Ландау, 3–8 апреля 2023 г. Фундаментальная и прикладная физика.

Доклад посвящен разработке сложной (состоящей из грубой и точной) системы наведения (компенсации угла) воздушной линии длиной 230 см для передачи высокостабильной оптической частоты. Активная компенсация фазовых шумов при полностью запущенной системе наведения позволяет подавить временную нестабильность частоты до значений менее 10–18 за время усреднения 10 с, при этом расширяя диапазон работы линии при угловом смещении потенциального объекта, принимающего излучение, с 0,3 до 3,15 градуса.

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Towards free-space ultrastable optical frequency transmission

2023PosterКсения Лискова, Alexey Legoshin, K. S. Kudeyarov, G. A. Vishnyakova +5

VII International Conference on Quantum Technologies (ICQT 2023)

Optical frequency transfer is essential for quantum technology applications, such as timekeeping and communication. To improve frequency transfer systems performance we have developed for both fiber optic and free-space optical links. Also an active pointing system has been developed and implemented for the atmospheric channel of ultra-stable optical frequency signal transfer making it capable of tracking moving objects. These advancements contribute to the expansion of quantum technologies through improved optical transfer systems.
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Towards free-space ultrastable optical frequency transfer

2023Conference talkКсения Лискова, Alexey Legoshin, K. S. Kudeyarov, G. A. Vishnyakova +5

VII International Conference on Quantum Technologies (ICQT 2023)

Nowadays optical frequency transfer has become an essential component for numerous quantum technology applications. There is a gradual increase in demand for such systems due to the rapid development of quantum technologies themselves, e. g. optical frequency transmission became crucial for high-precision timekeeping and communication systems relying on the frequency stability of quantum clocks that offer unparalleled accuracy, making ideal for metrology, navigation, and testing fundamental physical theories. Moreover, optical frequency transmission has already found popularity in such up-to-date topics as quantum communication and quantum cryptography.

For over 6 years, our laboratory has been developing various systems for the transmission of stabilized frequency signals. In 2017, we started with the elaboration of a phase noise compensation system in a 5-meter long optical fiber frequency transmission line and afterwards extended the line to 2.8 kilometers. Taking advantage of the result we also connected three of our laboratories with fiber optic cables with phase noise compensation systems to facilitate the process of comparing developed frequency standards. With an awareness of the fiber optic links applicability limitations (such as insufficient mobility and flexibility) we developed a 5-meter long free-space optical link with the same phase-noise compensation system in 2020 and increased its length to 17 meters with the addition of a precision pointing system in 2021.

Finally, in 2023, we introduced a 215-cm free-space optical transmission link with a flexible pointing system that enables dynamically stable tracking of moving objects: potentially drones or even satellites. The test scheme of this transfer system with defined upgrades is presented in Figure 1.

Phase noise compensation system for both fiber and free-space optical links The transmission link introduces phase noise into the signal. To compensate for corresponding frequency shifts, a laser beam used for transmission is split into two parts. The first part passes through a reference arm of an interferometer, while the second is transmitted to the receiver via an acousto-optic modulator (AOM1) and partly reflected back. The returned signal contains doubled link noise and is heterodyned with the reference beam. The resulting beat signal is used in a phase-locked loop that controls the frequency shift introduced by AOM1 and compensates the link noise.

Pointing system for free-space optical link To compensate for small high-frequency beam direction fluctuations, a precise (fast) pointing system was used, which includes a position-sensitive quadrant photodetector managing a mirror with two-coordinate galvanic control. To expand the pointing range, we implement a coarse (slow) pointing system by attaching the optical plate to an alt-azimuth telescope mount. The servo signal of the fast system is used to correct the angular velocity of the dynamic tripod rotation around two axes.

In the near future, we plan to extend the free-space link length and test the system in actual environments when pointing at a moving UAV. In addition, we plan to focus on processing the received noise signal in order to use it to obtain information about atmospheric parameters.

We strongly believe that the development of optical transmission systems is extremely useful for the expansion of quantum technologies.

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Система активного наведения для передачи ультрастабильных сигналов оптической частоты по воздушному каналу

2023Journal articleAlexey Legoshin, Ксения Лискова, K. S. Kudeyarov, G. A. Vishnyakova +5

Журнал Экспериментальной и Теоретической Физики

Разработана и создана система активного наведения для атмосферного канала передачи ультрастабильных оптических сигналов частоты, позволяющая существенно уменьшить геометрические отклонения передаваемого лазерного луча и обеспечить стабильную передачу в условиях движущегося отражателя, установленного в средней точке линии. Результаты тестирования работы системы подтверждают ее высокую эффективность и потенциал для применения в реальных условиях.
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Active Pointing System for the Transmission of Ultrastable Optical Frequency Signals through an Open-Air Link

2023Journal articleAlexey Legoshin, Ксения Лискова, K. S. Kudeyarov, G. A. Vishnyakova +5

Journal of Experimental and Theoretical Physics

An active pointing system has been developed and created for an atmospheric transfer link for ultrastable optical frequency signals. This system can significantly decrease the deviations of laser beam direction and ensure stable transmission under conditions of a moving reflector installed at the midpoint of the line. The results of testing the system confirm its high efficiency and potential for use under real conditions.
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Optimizing Modality Weights in Topic Models of Transactional Data

2022Journal articleK. Ya. Khrylchenko, Константин Вячеславович Воронцов

Automation and Remote Control

Modern natural language processing models such as transformers operate multimodal data. In the present paper, multimodal data is explored using multimodal topic modeling on transactional data of bank corporate clients. A definition of the importance of modality for the model is proposed on the basis of which improvements are considered for two modeling scenarios: preserving the maximum amount of information by balancing modalities and automatic selection of modality weights to optimize auxiliary criteria based on topic representations of documents. A model is proposed for adding numerical data to topic models in the form of modalities: each topic is assigned a normal distribution with learning parameters. Significant improvements are demonstrated in comparison with standard topic models on the problem of modeling bank corporate clients. Based on the topic representations of the bank’s customers, a 90-day delay on the loan is predicted.
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Incremental Learning of Topic Models for Finding Trend Topics in Scientific Publications

2022Journal articleN. A. Gerasimenko, A. S. Chernyavsky, M. A. Nikiforova, M. D. Nikitin +1

Doklady Mathematics

With a soaring number of scientific publications and rapid emergence of new directions and approaches, the scientific community faces the task of timely identification of trends. By a trend, we mean a semantically homogeneous topic characterized by a steady lexical kernel and a sharp, often exponential increase in the number of publications [1]. Examples of trends in machine learning are “LSTM,” “deep learning,” “word2vec,” “BERT,” and “fake news detection.” For real-time detection of trend topics from a stream of scientific publications, we use incremental methods of probabilistic topic modeling. An ARTM-based approach to early trend detection has been shown to outperform popular classical and neural network approaches to this task. A dataset of 91 trends for performance evaluation has been manually collected and made available for public use.

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Improving the Quality of Machine Translation Using the Reverse Model

2022Journal articleN. A. Skachkov, Константин Вячеславович Воронцов

Automation and Remote Control

Machine translation is a natural language text processing task that aims to automatically translate input text from one language into another language. The currently known machine translation models show a fairly high quality of translation between large languages, but for smaller language areas, represented by less data, the problem is still not solved. Different methods are used to deal with various errors in automatic translation systems. This paper discusses approaches that use translation models of reverse language directions and improve consistency between translations of the same text using direct and reverse translation models. The paper presents a general theoretical justification for such methods in terms of solving the likelihood maximization problem and also proposes a method for stable training of modern models using cyclic translations.
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Multiobjective Evaluation of Reinforcement Learning Based Recommender Systems

2022Conference paperAlexey Grishanov, Anastasia Ianina, Константин Вячеславович Воронцов

Movielens dataset has become a default choice for recommender systems evaluation. In this paper we analyze the best strategies of a Reinforcement Learning agent on Movielens (1M) dataset studying the balance between precision and diversity of recommendations. We found that trivial strategies are able to maximize ranking quality criteria, but useless for users of the recommendation system due to the lack of diversity in final predictions. Our proposed method stimulates the agent to explore the environment using the stochasticity of Ornstein-Uhlenbeck processes. Experiments show that optimization of the Ornstein-Uhlenbeck process drift coefficient improves the diversity of recommendations while maintaining high nDCG and HR criteria. To the best of our knowledge, the analysis of agent strategies in recommendation environments has not been studied excessively in previous works.
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