Translating Linguistic Terms: A Case Study of French and Russian Terminologies by Denis S. Zolotukhin

“…This paper explores the conceptual, semantic and formal features of linguistic terms that emerge in the process of selecting equivalents when translating scientific texts on linguistics from French to Russian and vice versa. …”
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Self-Nominations with Function of Anthroponym in Runet by V. V. Kaziaba

“…In pseudonymous self-names, the creative and playful functions of the language are realized, humorous and self-ironic connotations are found, the features of appearance, status, and political views are implicitly and explicitly imprinted. …”
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HMS-Net: A Hierarchical Multilabel Fine-Grained Ship Detection Network in Remote Sensing Images by Yunchao Yang, Zhengning Zhang, Pengming Feng, Yiming Yan, Guangjun He, Shaobo Liu, Pengyong Zhang, Haorao Gao

“…HMS-Net incorporates a parallel multilevel semantic feature extraction and fusion network, which leverages the multiscale region feature re-extraction module to perform effective feature re-extraction at different semantic levels. …”
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Psycholinguistic Specifics of Understanding by Ukrainian Students the Principles of Nomination of Linguocultural Models “clothing” in English and Ukrainian by Наталія Михальчук, Павло Левчук, Ернест Івашкевич, Людмила Ясногурська, Олена Чернякова

“…Productivity of students’ understanding of linguocultural units of the thematic group “clothing” in the Ukrainian language is determined by (a) the deep meaning of lexical units; (b) semantics and spatio-temporal meanings of linguocultural units; (c) syntactics of lexical units; (d) verb and noun basis of clothing nomination; (e) various connections between explicit concepts (metaphorical and metonymic transference); (f) assertive content of the nominative unit denoting “clothing”; (g) understanding of inferences, implications, intentions of the expressionж (h) explication of usualized (a priori) communicative meanings.…”
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MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection by Hantao Ding, Shengfeng Lou, Hairong Ye, Yanbing Chen

“…To address these issues, we introduce MT-CMVAD, a hierarchically structured Transformer architecture that makes two key technical contributions: (1) A Context-Aware Dynamic Fusion Module that leverages cross-modal attention with learnable gating coefficients to effectively bridge the gap between RGB and optical flow modalities through adaptive feature recalibration, significantly enhancing fusion performance; (2) A Multi-Scale Spatiotemporal Transformer that establishes global-temporal dependencies via dilated attention mechanisms while preserving local spatial semantics through pyramidal feature aggregation. …”
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THE WORLDVIEW FOUNDATIONS OF AZERBAIJANI COSMOGONIC AND ETHNOGONIC MYTHS by Kyzylgul Ya. Abbasova

“…Like myths in other cultures, Azerbaijani myths incorporate ethical elements, featuring evaluative components. However, the subject of evaluation is not the hero but rather the action, process, or deed – precisely these elements serve as the semantic dominants in the description of cosmogenesis and ethnogenesis. …”
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Entity extraction integrating lexical information for coal mine safety accidents by LYU Huilin, DONG Jiayao, YUAN Lin, LI Li

“…These vectors were then fused via a self-attention mechanism, which dynamically allocated weights to integrate RoBERTa-based character features and GloVe-based lexical features, yielding a composite vector enriched with lexical semantics. …”
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Dual-Stream Spatially Aware Transformer for Remote Sensing Image Captioning by Haifeng Sima, Xiangtao Ding, JianLong Wang, Mingliang Xu

“…However, due to the complex spatial layouts, occlusions, and overlapping objects in such images, caption generation is often challenged by semantic ambiguity. To address these issues, we propose a novel <italic>dual-stream spatially aware transformer</italic> (DSAT), which explicitly models both global and local spatial relationships to enhance spatial understanding. …”
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Declarative Speech Act as Form of Regulation in Russian Penitentiary Law of the Early 19^th Century by L. M. Golikov

“…The author defines their semantic-syntactic structure, presents classifying features of speech act, among which the conventionality and institutionality; identity of the expressed propositional content of legal reality; performativity and non-descriptiveness; ability to realize a directive perlocutive effect are considered relevant.…”
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SMS spam detection using BERT and multi-graph convolutional networks by Linjie Shen, Yanbin Wang, Zhao Li, Wenrui Ma

“…However, models like Convolutional Neural Networks and Recurrent Neural Networks struggle to capture global co-occurrence patterns and complex semantics, while transformer-based models like Bidirectional Encoder Representations from Transformers (BERT) lack explicit syntactic and co-occurrence modeling. …”
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Dual-Branch Diffusion Detection Model for Photovoltaic Array and Hotspot Defect Detection in Infrared Images by Ruide Li, Wenjun Yan, Chaoqun Xia

“…The proposed model encodes infrared images to extract semantic features, which are then processed through an PV array detection branch and a hotspot detection branch. …”
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HAN: Hierarchical Attention Network for Learning Latent Context-Aware User Preferences With Attribute Awareness by Hadise Vaghari, Mehdi Hosseinzadeh Aghdam, Hojjat Emami

“…Our model employs a Hierarchical Attention Network (HAN), which can grasp fine-grained relationships between item attributes in sessions and incorporates both temporal and semantic dependencies among items. By explicitly modeling user intentions and their evolving preferences, the HAN illustrates better how users act in behavior. …”
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A Novel Framework for Saraiki Script Recognition Using Advanced Machine Learning Models (YOLOv8 and CNN) by Hafiz Muhammad Raza Ur Rehman, Syed Arfan Haider, Hiba Faisal, Kook-Yeol Yoo, M. Z. Jhandir, Gyu Sang Choi

“…On the other hand, machine learning is the study of how to teach machines to learn and predict using data instead of explicit programming. By combining these two domains, machine learning has emerged as a potent instrument in linguistics, improving our capacity to comprehend semantics, analyze verbal patterns, and even simulate human-like replies. …”
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LLM-MalDetect: A Large Language Model-Based Method for Android Malware Detection by Ruirui Feng, Hui Chen, Shuo Wang, Md Monjurul Karim, Qingshan Jiang

“…To address this gap, we introduce LLM-MalDetect, a novel framework that improves LLM-based APK analysis by explicitly modeling semantic dependencies and leveraging structured prompt engineering for optimized detection. …”
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Developing clinical reasoning along the cognitive continuum: a mixed methods evaluation of a novel Clinical Diagnosis Assessment by Lucinda E. Ainge, Amanda K. Edgar, Jacqueline M. Kirkman, James A. Armitage

“…Therefore, we designed the Clinical Diagnosis Assessment, an assessment for learning, to explicitly train Type 1 and Type 2 reasoning skills in optometry students. …”
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Object Ontologies as a Priori Models for Logical-Probabilistic Machine Learning by D. N. Gavrilin, A.V. Mantsivoda

“…Logical-probabilistic machine learning (LPML) is an AI method able to explicitly work with a priori knowledge represented in data models. …”
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POLITICAL CORRECTNESS IN POLITICAL DISCOURSE: THEORY OF IDEOLOGICAL ASPECT by Yuliia G. Karachun, Nataliia V. Davydenko

“…The study employs general scientific methods (analysis, generalization, systematization of scholarly literature on the issue under consideration), and special linguistic methods (method of distributional analysis, used to highlight the main semantic groups of politically correct vocabulary; elements of the component analysis, necessary to identify components of the meaning of politically correct vocabulary; method of linguostylistic analysis, used to study the functional features of politically correct vocabulary based on ideology). …”
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Distributed Sparse Manifold-Constrained Optimization Algorithm in Linear Discriminant Analysis by Yuhao Zhang, Xiaoxiang Chen, Manlong Feng, Jingjing Liu

“…In order to improve the accuracy and robustness of linear discriminant analysis, this paper proposes a new distributed sparse manifold constraint (DSC) optimization LDA method, called DSCLDA, which introduces <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mrow><mn>2</mn><mo>,</mo><mn>0</mn></mrow></msub></semantics></math></inline-formula>-norm regularization for local sparse feature representation and manifold regularization for global feature constraints. …”
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SYNCode: Synergistic Human–LLM Collaboration for Enhanced Data Annotation in Stack Overflow by Meng Xia, Shradha Maharjan, Tammy Le, Will Taylor, Myoungkyu Song

“…This framework is designed explicitly to facilitate collaboration between humans and LLMs for annotating complex, code-centric datasets such as Stack Overflow. …”
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Apple Detection via Near-Field MIMO-SAR Imaging: A Multi-Scale and Context-Aware Approach by Yuanping Shi, Yanheng Ma, Liang Geng

“…DSPP employs a learnable adaptive mechanism to dynamically adjust multi-scale feature representations, enhancing sensitivity to apple targets of varying sizes and distributions; RFN uses a multi-round iterative feature fusion strategy to gradually refine semantic consistency and stability, improving the robustness of feature representation under weak texture and high noise scenarios; and the CAFE module, based on attention mechanisms, explicitly models global and local associations, fully utilizing the scene context in texture-poor SAR conditions to enhance the discriminability of apple targets. …”
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