BALI—A Benchmark for Accelerated Language Model Inference by Lena Jurkschat, Preetam Gattogi, Sahar Vahdati, Jens Lehmann

“…The rise of Large Language Models (LLMs) has revolutionized natural language processing, enabling advancements across diverse applications, including chatbots, live translators, content generation, virtual assistants, and domain-specific automation tools. …”
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Mapping two decades of research in rheumatology-specific journals: a topic modeling analysis with BERTopic by Alfredo Madrid-García, Dalifer Freites-Núñez, Beatriz Merino-Barbancho, Inés Pérez Sancristobal, Luis Rodríguez-Rodríguez

“…To better characterize the research landscape and advances in rheumatology, automatic and efficient approaches based on natural language processing (NLP) should be used. Objectives: The objective of this study is to use topic modeling (TM) techniques to uncover key topics and trends in rheumatology research conducted in the last 23 years. …”
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Patient Perspectives on Conversational Artificial Intelligence for Atrial Fibrillation Self-Management: Qualitative Analysis by Ritu Trivedi, Tim Shaw, Brodie Sheahen, Clara K Chow, Liliana Laranjo

“…The 6-month intervention consisted of fully automated conversational AI phone calls (with speech recognition and natural language processing) that assessed patient health and provided self-management support and education. …”
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Bridging language gaps: The role of NLP and speech recognition in oral english instruction by Parul Dubey, Pushkar Dubey, Rohit Raja, Sapna Singh Kshatri

“…The Natural Language Processing (NLP) and speech recognition have transformed language learning by providing interactive and real-time feedback, enhancing oral English proficiency. …”
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Transformer-Based Amharic-to-English Machine Translation With Character Embedding and Combined Regularization Techniques by Surafiel Habib Asefa, Yaregal Assabie

“…It is also an under-resourced language, presenting significant challenges for natural language processing tasks like machine translation. The primary challenges include the scarcity of parallel data, which increases the risk of overfitting and limits the model’s ability to generalize effectively, and the complex morphology of Amharic, which further complicates learning patterns in translation tasks. …”
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Context-Aware Multimodal Fusion with Sensor-Augmented Cross-Modal Learning: The BLAF Architecture for Robust Chinese Homophone Disambiguation in Dynamic Environments by Yu Sun, Yihang Qin, Wenhao Chen, Xuan Li, Chunlian Li

“…Chinese, a tonal language with inherent homophonic ambiguity, poses significant challenges for semantic disambiguation in natural language processing (NLP), hindering applications like speech recognition, dialog systems, and assistive technologies. …”
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SMOTE-LOF for noise identification in imbalanced data classification by Asniar, Nur Ulfa Maulidevi, Kridanto Surendro

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Model Semantic Attention (SemAtt) With Hybrid Learning Separable Neural Network and Long Short-Term Memory to Generate Caption by Agus Nursikuwagus, Rinaldi Munir, Masayu L. Khodra, Deshinta Arrova Dewi

“…Image captioning is a hot topic that combines a multidiscipline task between computer vision and natural language processing. One of the tasks in the geological field is to make descriptions from the images of geological rocks. …”
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Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…In healthcare, AI encompasses various subfields, including machine learning, deep learning, natural language processing, and expert systems. In the specific domain of onychology, AI presents a promising avenue for diagnosing nail disorders, analyzing intricate patterns, and improving diagnostic accuracy. …”
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Combining Autoregressive Models and Phonological Knowledge Bases for Improved Accuracy in Korean Grapheme-to-Phoneme Conversion by Sung-Ki Choi, Hyuk-Chul Kwon, Minho Kim

“…Recent advances in deep learning have highlighted the importance of Grapheme-to-Phoneme (G2P) conversion in natural language processing and speech synthesis. Korean exhibits complex phonological changes such as liaison, initial sound law, and consonant assimilation, making it challenging to handle all exceptional patterns with simple models alone. …”
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ATTRIBUTION OF MEDIA TEXTS BASED ON A TRAINED NATURAL LANGUAGE MODEL AND LINGUISTIC ASSESSMENT OF IDENTIFICATION QUALITY by Vladimir A. Klyachin, Ekaterina V. Khizhnyakova

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Semantic processing of argument structure during naturalistic story listening: Evidence from computational modeling on fMRI by Tianze Xu, Jixing Li, Xiaoming Jiang

“…The methodological framework integrated a general linear model (GLM) analysis of the fMRI data with computational modeling using natural language processing algorithms. These components were integrated using representational similarity analysis (RSA), allowing us to assess the relatedness of two symbolic computational models—one relying on syntactic information from parse trees and the other based on semantic selectional preference information of verbs—to brain activities. …”
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The Effect of Asymmetric Transistor Aging on Systolic Arrays for Mission Critical Machine Learning Applications by Firas Ramadan, Gil Shomron, Freddy Gabbay

“…Deep neural networks (DNNs) excel in various applications, such as computer vision, natural language processing, and other mission-critical systems. …”
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Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study by Juan DAlotto DAlotto, Claudia Pons, Leandro Antonelli

“…There is also a progressive adoption of Natural Language Processing and machine learning techniques.   …”
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Decision Support System for Evaluating Corpus-Based Word Lists for Use in English Language Teaching Contexts by Ruoxi Yin, Chunmei Zhu, Jiuyang Zhu

“…This study proposes a Decision Support System (DSS) that integrates corpus linguistics, Natural Language Processing (NLP), and machine learning to generate optimized vocabulary lists tailored for ELT. …”
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Investigating Offensive Language Detection in a Low-Resource Setting with a Robustness Perspective by Israe Abdellaoui, Anass Ibrahimi, Mohamed Amine El Bouni, Asmaa Mourhir, Saad Driouech, Mohamed Aghzal

“…Moroccan Darija, a dialect of Arabic, presents unique challenges for natural language processing due to its lack of standardized orthographies, frequent code switching, and status as a low-resource language. …”
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Enhancing Disaster Situation Awareness Through Multimodal Social Media Data: Evidence from Typhoon Haikui by Songfeng Gao, Tengfei Yang, Yuning Xu, Naixia Mou, Xiaodong Wang, Hao Huang

“…We employed the ERNIE natural language processing model to complement the Deeplab v3+ deep learning image semantic segmentation model for extracting disaster damage information from social media. …”
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Analysis of Short Texts Using Intelligent Clustering Methods by Jamalbek Tussupov, Akmaral Kassymova, Ayagoz Mukhanova, Assyl Bissengaliyeva, Zhanar Azhibekova, Moldir Yessenova, Zhanargul Abuova

“…Based on the findings, the study recommends the optimum choice and use of clustering methods for different short texts and natural language processing operations. The applications of these methods in industrial and educational settings, where successful text handling and categorization are critical, are also addressed. …”
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A VAN-Based Multi-Scale Cross-Attention Mechanism for Skin Lesion Segmentation Network by Shuang Liu, Zeng Zhuang, Yanfeng Zheng, Simon Kolmanic

“…To address this problem, the Transformer from the field of natural language processing (NLP) was introduced to the image segmentation field. …”
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Large language models in oncology: a review by Fei-Fei Liu, David Chen, Srinivas Raman, Rod Parsa, Karl Swanson, John-Jose Nunez, Andrew Critch, Danielle S Bitterman

“…Large language models (LLMs) have demonstrated emergent human-like capabilities in natural language processing, leading to enthusiasm about their integration in healthcare environments. …”
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