A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

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The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

“…It outputs both the probability that the object is present in its limited area and a set of “instance parameters” that can include the exact pose, lighting, and deformation of the visual object relative to an implicitly defined canonical version of this object. …”
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Graph Contrastive Pre-training for Anti-money Laundering by Hanbin Lu, Haosen Wang

“…Abstract Anti-money laundering (AML) is vital to maintaining financial markets, social stability, and political authority. At present, many studies model the AML task as the graph and leverage graph neural network (GNN) for node/edge classification. …”
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Dual Branch Graph Representation Learning-Based Approach for Next Point-of-Interest Recommendation by Guoning Lv, Min Gao

“…In this paper, we observe that existing methods for this task have a fundamental limitation: they find it difficult to comprehensively model the associations between POIs from both explicit and implicit perspectives. To bridge this gap, we present a new method DBGR. …”
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Anomaly Detection Over Multi-Relational Graphs Using Graph Structure Learning and Multi-Scale Meta-Path Graph Aggregation by Chi Zhang, Junho Jeong, Jin-Woo Jung

“…Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. …”
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Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals by Sowmya Vijayakumar, Ronan Flynn, Peter Corcoran, Niall Murray

“…This article proposes using physiological signals to assess the QoE of immersive multimedia applications, which provides insights into users’ emotional and cognitive states. Specifically, we present an implicit evaluation of user QoE in terms of perceived quality, sense of presence, and user content preference using a publicly accessible database. …”
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Let’s Practice Better... on Cats: Description and Visualisation of Artistic Images in Generative AI Models by Ruslan Khandogin, Nina S. Proner

“…The article emphasises that the literary text is at the top of the hierarchy of cultural texts; it is characterised by intentionality and coherence and represents a complex semantic field where key words and images interact with the explicit and implicit contexts. The study examines and analyses the visualised images of Cheshire Cat, Cat Behemoth and Tomcat Murr created by the authors with the use of three generative neural networks: Stable Diffusion, Dall‑E and Kandinsky. …”
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Effects of Transcranial Alternating Current Stimulation on Cognitive Functions in Healthy Young and Older Adults by Daria Antonenko, Miriam Faxel, Ulrike Grittner, Michal Lavidor, Agnes Flöel

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Understanding implicature as an inner simulation of the speaker's context retrieval by Shingo Tokimoto, Naoko Tokimoto

“…Although pragmatic inference is generally assumed to support the comprehension of such implicit intentions, the underlying neural mechanisms remain poorly understood. …”
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Time course of indirect reply comprehension in the young and older adults: an event-related potential study by Wangshu Feng, Xiaokun Zhang, Weijuan Wang, Lin Fan

“…As individuals age, their ability to make efficient and accurate pragmatic inferences may decline, leading to communication difficulties.ObjectivesThis study examined the cognitive aging phenomenon of pragmatic inference and its neural mechanisms using EEG recordings.MethodsParticipants were presented with dialogues involving direct and indirect replies and were required to judge the speaker's intended meaning based on the context.ResultsYounger participants outperformed older participants in task accuracy for indirect replies. …”
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Proto-arithmetic abilities in zebrafish (Danio rerio) by Davide Potrich, Lorenza Montel, Gionata Stancher, Greta Baratti, Giorgio Vallortigara, Valeria Anna Sovrano

“…The increasing use of zebrafish (Danio rerio) as a model for studying the neural bases of numerical/quantity abilities pushes toward the development of fast and reliable behavioral tasks for this species. …”
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Visuospatial sequence learning without seeing. by Clive R Rosenthal, Christopher Kennard, David Soto

“…Learning sequential associations between non-adjacent visual stimuli (higher-order visuospatial dependencies) can occur either with or without awareness (explicit vs. implicit learning) of the products of learning. Existing behavioural and neurocognitive studies of explicit and implicit sequence learning, however, are based on conscious access to the sequence of target locations and, typically, on conditions where the locations for orienting, or motor, responses coincide with the locations of the target sequence.…”
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The Role of the Sentence Constraint in New Word Acquisition While Reading in Adolescents: The ERP N400 and P600 and Reading-Related Skills by Marina Norkina, Anna Rebreikina, Maksim Markevich, Elena L. Grigorenko

“…Our study reveals that while the accuracy of word recognition was at a chance level, adolescents had faster responses to words learned in high-constraining contexts compared to words from low-constraining contexts. Neural responses were influenced by context, with explicit recollection processes reflected in the P600 being modulated by the type of sentence constraint, while implicit familiarity related to the N400 did not show this effect. …”
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Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles by Xiuqin Wang, Jun Geng, Zhiyuan Li

“…A two-way recurrent neural network based on the gated recurrent unit is used to extract a sequence of note feature vectors of different styles, and a one-dimensional convolutional neural network is used to predict the intensity of the extracted note feature vector sequence for a specific style, which better learns the intensity variation of different styles of MIDI music.…”
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Application of deep learning methods for online beam optics and coupling feedback in synchrotron light sources by Liyuan Tan, Shouzhi Xuan, Yihao Gong, Xinzhong Liu, Xu Wu, Shunqiang Tian, Wenzhi Zhang

“…A deep learning network has been applied to extract phase advance and betatron coupling information implicit in TBT data. Subsequently, these data were fed into a multilayer neural network for rapid modeling and correction. …”
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Toward Data-Driven Collaborative Dialogue Systems: The JILDA Dataset by Irene Sucameli, Alessandro Lenci, Bernardo Magnini, Manuela Speranza, Maria Simi

“…Today’s goal-oriented dialogue systems are designed to operate in restricted domains and with the implicit assumption that the user goals fit the domain ontology of the system. …”
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Social knowledge about others is anchored to self-knowledge in the hippocampal formation. by Marta Rodríguez Aramendía, Mariachiara Esposito, Raphael Kaplan

“…Here, we test if a prominent heuristic involving an implicit reliance on self-knowledge when rating others, egocentric anchoring-and-adjustment, is present in the HF when relational information about different social entities is retrieved. …”
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Advanced beamforming and reflection control in intelligent reflecting surfaces with integrated channel estimation by Sakhshra Monga, Anmol Rattan Singh, Nitin Saluja, Chander Prabha, Shivani Malhotra, Asif Karim, Md. Mehedi Hassan

“…This is achieved by mapping incoming pilot signals and data, including user positions, with a deep neural network (DNN), guiding an optimal setup. User interactions are captured using a permutation‐invariant graph neural network (GNN) architecture. …”
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Uncertainty Estimation in Unsupervised MR-CT Synthesis of Scoliotic Spines by Enamundram Naga Karthik, Farida Cheriet, Catherine Laporte

“…Uncertainty estimations through approximate Bayesian inference provide interesting insights to deep neural networks' behavior. In unsupervised learning tasks, where expert labels are unavailable, it becomes ever more important to critique the model through uncertainties. …”
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LLM-CDM: A Large Language Model Enhanced Cognitive Diagnosis for Intelligent Education by Xin Chen, Jin Zhang, Tong Zhou, Feng Zhang

“…Specifically, this study first inputs exercise texts into a large language model and develops an innovative prompting method to facilitate deep mining of implicit knowledge concepts within these texts by the model. …”
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