Increasing the ethnic diversity of senior leadership within the English National Health Service: using an artificial intelligence approach to evaluate inclusive recruitment strateg... by Sarindi Aryasinghe, Catalina Carenzo, Kerri-Ann Barnett, Rabia Khalid, Koya Greenaway-Harvey, Colleen Sherlock, Louise Clark, Kevin Croft, Tim Orchard, Erik Mayer

“…Artificial intelligence tools, such as natural language processing, provide effective methods to evaluate and enhance EDI recruitment initiatives by analysing routinely collected recruitment data to identify areas for improvement and establish best practices.…”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Besides peer review, AI has also improved the editorial process by employing language processing models that assist authors in manuscript editing. …”
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MFSM: Chinese-English sentence alignment based on multi- feature self-attention mechanism fusion by Baolong Li

“…Bilingual parallel corpora is a very important basic resource in the research field of natural language processing based on statistics. There are cross alignment and empty alignment in Chinese-English bilingual text, it is easy to affect the effect of Chinese-English sentence alignment. …”
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Sentiment Analysis of Product Reviews Using Fine-Tuned LLaMa-3 Model: Evaluation with Comprehensive Benchmark Metrics by Wang Yili

“…Sentiment analysis, a crucial subfield of natural language processing, enables businesses and policymakers to understand public emotions and opinions, essential for crafting effective strategies across industries like marketing and customer service. …”
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Business Intent and Network Slicing Correlation Dataset from Data-Driven Perspective by Jie Li, Sai Zou, Yanglong Sun, Hongfeng Gao, Wei Ni

“…We utilize natural language processing techniques based on named entity recognition and third-party data analysis tools such as DataProfiler to validate the data quality of BINS, confirming its reliability. …”
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Assessing the Extent of Integration of Artificial Intelligence in Teaching and Learning at Kenyan Universities by Callen Nyamwange

“…Data were collected from students across diverse programs through the Learning Management Systems (LMS) and analyzed using AI-powered learning analytics and natural language processing (NLP) tools. Key metrics included course completion rates, assignment engagement, and assessment performance. …”
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Towards Malay named entity recognition: an open-source dataset and a multi-task framework by Yingwen Fu, Nankai Lin, Zhihe Yang, Shengyi Jiang

“…Named entity recognition (NER) is a key component of many natural language processing (NLP) applications. The majority of advanced research, however, has not been widely applied to low-resource languages represented by Malay due to the data-hungry problem. …”
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Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM by Dongmei Zhu

“…Abstract This study aims to enhance computers’ ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. It proposes a metaphor recognition algorithm that combines a Convolutional Neural Network (CNN) with a Support Vector Machine (SVM). …”
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American social media users have ideological differences of opinion about the War in Ukraine by William G. Nomikos, Dahjin Kim, Gechun Lin

“…Then, we apply a natural language processing model specifically designed for short texts to classify the tweets into clusters that we hand code into substantive topics. …”
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Enhancing Intent Classifier Training with Large Language Model-generated Data by Alberto Benayas, Sicilia Miguel-Ángel, Marçal Mora-Cantallops

“…Intent classification is essential in Natural Language Processing, serving applications like virtual assistants and customer service by categorizing user inputs into predefined classes. …”
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Identification of Writing Strategies in Educational Assessments with an Unsupervised Learning Measurement Framework by Cheng Tang, Jiawei Xiong, George Engelhard

“…This study proposes a framework that leverages natural language processing and unsupervised machine learning techniques to measure, identify, and classify examinees’ writing strategies. …”
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CMap: a database for mapping job titles, sector specialization, and promotions across 24 sectors by Shehryar Subhani, Shahan Ali Memon, Bedoor AlShebli

“…We introduce Career Map (CMap), a novel, large-scale dataset spanning 24 industry sectors, designed to support the study of job specialization, sectoral concentration, and career advancement. Using natural language processing techniques and large language models, we standardize 5.2 million job titles into 123 thousand unique titles and propose a Specialization Index to quantify how concentrated a given title is within a sector. …”
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Policy brief: Improving national vaccination decision-making through data by Sandra Evans, Joe Schmitt, Dipak Kalra, Tomislav Sokol, Daphne Holt

“…Rapid strides in artificial intelligence, such as machine learning and natural language processing, can enhance data analysis, conceptual modelling, and real-time surveillance. …”
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Cancer type, stage and prognosis assessment from pathology reports using LLMs by Rachit Saluja, Jacob Rosenthal, Annika Windon, Yoav Artzi, David J. Pisapia, Benjamin L. Liechty, Mert R. Sabuncu

“…Abstract Large Language Models (LLMs) have shown significant promise across various natural language processing tasks. However, their application in the field of pathology, particularly for extracting meaningful insights from unstructured medical texts such as pathology reports, remains underexplored and not well quantified. …”
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Assessing the Value of Transfer Learning Metrics for Radio Frequency Domain Adaptation by Lauren J. Wong, Braeden P. Muller, Sean McPherson, Alan J. Michaels

“…The use of transfer learning (TL) techniques has become common practice in fields such as computer vision (CV) and natural language processing (NLP). Leveraging prior knowledge gained from data with different distributions, TL offers higher performance and reduced training time, but has yet to be fully utilized in applications of machine learning (ML) and deep learning (DL) techniques and applications related to wireless communications, a field loosely termed radio frequency machine learning (RFML). …”
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Text Embedding Augmentation Based on Retraining With Pseudo-Labeled Adversarial Embedding by Myeongsup Kim, Pilsung Kang

“…Pre-trained language models (LMs) have been shown to achieve outstanding performance in various natural language processing tasks; however, these models have a significantly large number of parameters to handle large-scale text corpora during the pre-training process, and thus, they entail the risk of overfitting when fine-tuning for small task-oriented datasets is conducted. …”
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Multidimensional Model of Sebastian Unger’s Idiostyle in Poetic Creativity: Corpus Analysis and NLP Methods by Tetiana Hromko, Liudmyla Panchuk

“…The article presents a multidimensional model of Sebastian Unger’s idiostyle based on corpus analysis and natural language processing (NLP) methods. The study is based on a structured approach to the analysis of authorial style, comprising text certification, thematic modeling, and stylometric evaluation. …”
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A Grouping Hotel Recommender System Based on Deep Learning and Sentiment Analysis by Fatemeh Abbasi, Ameneh Khadivar, Mohsen Yazdinejad

“…The proposed system uses Natural Language Processing (NLP) and supervised classification approach to analyze sentiments and extract implicit features. …”
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The Ecosystem of AI-Driven Robotics in Pediatric Neurorehabilitation by Tole Sutikno, Lina Handayani

“…Moreover, the inclusion of natural language processing and facial expression analysis warrants careful consideration, as it sets the stage for more nuanced interactions between robots and pediatric patients, thereby fostering a therapeutic environment that is both responsive and empathetic. …”
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Text Classification of News Using Transformer-based Models for Portuguese by Isabel N. Santana, Raphael S. Oliveira, Erick G. S. Nascimento

“…This work proposes the use of a fine-tuned Transformers-based Natural Language Processing (NLP) model called BERTimbau to generate the word embeddings from texts published in a Brazilian newspaper, to create a robust NLP model to classify news in Portuguese, a task that is costly for humans to perform for big amounts of data. …”
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