Sequence-to-Sequence Text Generation with Discrete Diffusion Models by JIANG Hang, CAI Guoyong, LI Sihui

“…Achieving high-quality Seq2Seq text generation with low latency remains a persistent challenge in the field of natural language processing. To this end, this paper simplifies the training process of the discrete diffusion model by deriving an upper bound on the training objective, and subsequently introduces and modifies the mask-and-predict decoding strategy from the conditional mask language model as the inference algorithm of the diffusion model. …”
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Towards human-AI collaboration in the competency-based curriculum development process: The case of industrial engineering and management education by Antonio Padovano, Martina Cardamone

“…Through a stepwise methodology based on semantic analysis, text mining, natural language processing (NLP) models, informetrics approaches, and clustering algorithms, we provide data-driven insights to inform the curriculum development process. …”
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LoRA-Adv: Boosting Text Classification in Large Language Models Through Adversarial Low-Rank Adaptations by Hong Ye, Xialin Xie, Fenlong Xie, Jun Zuo, Chunyan Bu

“…Low-rank adaptation (LoRA), a paradigm bridging the gap between large language models and fine-tuning, has demonstrated effectiveness across various natural language processing tasks. The LoRA algorithm updates only a small number of model parameters, significantly reducing the consumption of computational resources. …”
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Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll, Hongxiang Feng

“…Compared with traditional single-factor analysis methods, the proposed framework shows marked improvements in Natural Language Processing (NLP) efficiency, classification precision, and systematic interpretation of cross-factor correlations. …”
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Effective Multi-Class Sentiment Analysis Using Fine-Tuned Large Language Model with KNIME Analytics Platform by Jin-Ching Shen, Nai-Jing Su, Yi-Bing Lin

“…The rapid advancement of large language models (LLMs) has revolutionized natural language processing (NLP), yet fine-tuning these models for domain-specific applications remains a resource-intensive challenge. …”
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Physics-Informed Neural Networks for the Structural Analysis and Monitoring of Railway Bridges: A Systematic Review by Yuniel Martinez, Luis Rojas, Alvaro Peña, Matías Valenzuela, Jose Garcia

“…Through natural language processing (NLP) and trend mapping, this review evidences a growing but fragmented research landscape. …”
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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

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A Machine Learning-Based Computational Methodology for Predicting Acute Respiratory Infections Using Social Media Data by Jose Manuel Ramos-Varela, Juan C. Cuevas-Tello, Daniel E. Noyola

“…The first two stages focuses on identifying the best-performing predictive models, while the third stage includes Natural Language Processing (NLP) algorithms for tweet selection. …”
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Compilation, Analysis and Application of a Comprehensive Bangla Corpus KUMono by Aysha Akther, Md. Shymon Islam, Hafsa Sultana, A. K. Z. Rasel Rahman, Sujana Saha, Kazi Masudul Alam, Rameswar Debnath

“…Research in Natural Language Processing (NLP) and computational linguistics highly depends on a good quality representative corpus of any specific language. …”
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Benefits and risks of ChatGPT in future education by Baltezarević Radoslav, Baltezarević Ivana

“…Created by OpenAI, ChatGPT is an artificial intelligence (AI) chatbot that makes use of natural language processing (NLP). ChatGPT analyses enormous volumes of data using machine learning (ML) to offer the necessary content and simply respond to queries in a conversational manner. …”
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Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review by Martina Feierabend, Julius Michael Wolfgart, Maximilian Praster, Marina Danalache, Filippo Migliorini, Ulf Krister Hofmann

“…Abstract Artificial intelligence (AI), with its technologies such as machine perception, robotics, natural language processing, expert systems, and machine learning (ML) with its subset deep learning, have transformed patient care and administration in all fields of modern medicine. …”
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Optimising window size of semantic of classification model for identification of in-text citations based on context and intent. by Arshad Iqbal, Abdul Shahid, Muhammad Roman, Muhammad Tanvir Afzal, Umair Ul Hassan

“…Deep learning-based word embedding techniques have garnered significant attention and found application in various Natural Language Processing (NLP) tasks, including text classification, sentiment analysis, and citation analysis. …”
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Explainable Pre-Trained Language Models for Sentiment Analysis in Low-Resourced Languages by Koena Ronny Mabokela, Mpho Primus, Turgay Celik

“…While state-of-the-art Afrocentric pre-trained language models (PLMs) have been developed for various natural language processing (NLP) tasks, their applications in eXplainable Artificial Intelligence (XAI) remain largely unexplored. …”
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A novel approach for multiclass sentiment analysis on Chinese social media with ERNIE-MCBMA by Youyang Sun, Ziyi Yu, Yuyu Sun, Yaqing Xu, Boming Song

“…Conducting sentiment analysis on Weibo posts using natural language processing techniques is crucial for market research and public opinion observation, holding significant commercial and societal importance. …”
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Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection by Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, the CMS-HCAL Collaboration

“…Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. …”
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An NLP-Based Framework to Spot Extremist Networks in Social Media by Andrés Zapata Rozo, Daniel Díaz-López, Javier Pastor-Galindo, Félix Gómez Mármol, Umit Karabiyik

“…Thus, this paper proposes a framework based on natural language processing (NLP) that detects and inspects supposed HSM actions to support law enforcement agencies (LEAs) in the prevention of cyberterrorism. …”
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Integrating Abstract Meaning Representation to Enhance Transformer-Based Image Captioning by Nguyen Van Thinh, Tran Lang, Van The Thanh

“…Meanwhile, Abstract Meaning Representation (AMR), a form of abstract semantic representation, has been successfully applied in various natural language processing tasks. However, exploiting AMR in multimodal contexts, particularly for image captioning, remains largely unexplored. …”
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POTENTIAL OF MACHINE TRANSLATION IN MUSEUM MEDIA DISCOURSE: ANALYSIS OF MODERN BROWSER SYSTEMS by Vera A. Mityagina, Anna A. Novozhilova, Anna P. Naumova

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Exploring Legislative Textual Data in Brazilian Portuguese: Readability Analysis and Knowledge Graph Generation by Gisliany Lillian Alves de Oliveira, Breno Santana Santos, Marianne Silva, Ivanovitch Silva

“…Ultimately, this study advances legal artificial intelligence by providing insights into Brazilian legislative texts and promoting transparency and accessibility through natural language processing techniques.…”
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Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach by Mohammad Heydari, Babak Teimourpour

“…Keyword extraction is a crucial task in natural language processing. In this study, we demonstrated that high-precision extraction of keywords from Instagram posts in the Persian language can be achieved using unsupervised word co-occurrence methods without resorting to conventional techniques such as clustering or pre-trained models. …”
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