The Machine Translation (MT) of Proverbs in the ENG-PL Language Pair by Romaniuk-Cholewska Dominika

“…Furthermore, the study revealed errors typical of translation tools based on large language models such as ChatGPT and Google Bard.…”
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How digital transformation can influence workflows, teaching practices and curricula in (bio)process science and engineering—An interview series with stakeholders by J. F. Buyel

“…Abstract A massive digital transformation is underway in biotechnology and process engineering fueled by recent advances in machine learning and so‐called artificial intelligence, especially in the large language model field (e.g., ChatGPT). Training courses and curricula will need to adapt to keep pace, but the speed of progress is such that guidelines for the implementation of a digital transformation are probably already outdated. …”
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A prospective pragmatic evaluation of automatic trial matching tools in a molecular tumor board by Lilia Gueguen, Louise Olgiati, Clément Brutti-Mairesse, Alric Sans, Vincent Le Texier, Loic Verlingue

“…We showed that using a Large Language Model on the patients’ molecular reports could improve the performance by up to 5%. …”
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Evaluating simulated teaching audio for teacher trainees using RAG and local LLMs by Ke Fang, Ci Tang, Jing Wang

“…This paper introduces a Retrieval-Augmented Generation (RAG) framework constructed using various open-source tools (such as FastChat for model inference and Whisper for speech-to-text) combined with a local large language model (LLM) for audio analysis of simulated teaching. …”
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Hyperbolic Graph Convolutional Network Relation Extraction Model Combining Dependency Syntax and Contrastive Learning by Jinzhe Li

“…Abstract In current relation extraction tasks, when the input sentence structure is complex, the performance of in-context learning methods based on large language model is still lower than that of traditional pre-train fine-tune models. …”
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Improving Text Recognition Accuracy for Serbian Legal Documents Using BERT by Miloš Bogdanović, Milena Frtunić Gligorijević, Jelena Kocić, Leonid Stoimenov

“…Our approach integrates three different components to provide high-quality results: a BERT-based large language model built specifically for Serbian legal texts, a high-quality open-source optical character recognition (OCR) model, and a word-level similarity measure for Serbian Cyrillic developed for this research and used for generating necessary correction suggestions. …”
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Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

“…This framework integrates the QTRAN algorithm with a large language model (LLM) for efficient region decomposition and employs graph convolutional networks (GCNs) combined with self-attention mechanisms to adeptly manage inter-subregion relationships. …”
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Measuring China’s Policy Stringency on Climate Change for 1954–2022 by Bo Li, Enxian Fu, Shuhao Yang, Jiaying Lin, Wei Zhang, Jian Zhang, Yaling Lu, Jiantong Wang, Hongqiang Jiang

“…This paper employs an integrated framework comprising lexicon, text analysis, machine learning, and large-language model applied to multi-source data to quantify China’s policy stringency on climate change (PSCC) from 1954 to 2022. …”
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Evaluating ChatGPT in Generating Feedback on Content and Organization Components of EFL Compare and Contrast Essays by Berkan Çelik, Behice Ceyda Cengiz, Amine Hatun Ataş

“…ChatGPT, an innovative large language model that has impressed worldwide audiences with its exceptional generative capabilities, is now positioned to significantly transform the field of education. …”
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Evaluating AI performance in nephrology triage and subspecialty referrals by Priscilla Koirala, Charat Thongprayoon, Jing Miao, Oscar A. Garcia Valencia, Mohammad S. Sheikh, Supawadee Suppadungsuk, Michael A. Mao, Justin H. Pham, Iasmina M. Craici, Wisit Cheungpasitporn

“…This study evaluates the utility of ChatGPT, a large language model, in triaging nephrology cases through simulated real-world scenarios. …”
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DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios by Yanjun Sun, Yue Qiu, Yoshimitsu Aoki

“…Specifically, we have designed ten scenarios that simulate the challenges of dynamic navigation and developed a dedicated dataset of 11,261 instances using the CARLA simulator (ver.0.9.13) and large language model to provide realistic training conditions. …”
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Application of Generative Artificial Intelligence Models for Accurate Prescription Label Identification and Information Retrieval for the Elderly in Northern East of Thailand by Parinya Thetbanthad, Benjaporn Sathanarugsawait, Prasong Praneetpolgrang

“…Two model architectures were explored: a Two-Stage Optical Character Recognition (OCR) and Large Language Model (LLM) pipeline combining EasyOCR with Qwen2-72b-instruct and a Uni-Stage Visual Question Answering (VQA) model using Qwen2-72b-VL. …”
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The Self-Perception and Political Biases of ChatGPT by Jérôme Rutinowski, Sven Franke, Jan Endendyk, Ina Dormuth, Moritz Roidl, Markus Pauly

“…This contribution analyzes the self-perception and political biases of OpenAI’s Large Language Model ChatGPT. Considering the first small-scale reports and studies that have emerged, claiming that ChatGPT is politically biased towards progressive and libertarian points of view, this contribution is aimed at providing further clarity on this subject. …”
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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

“…The creation of effective systems for filtering media texts is due to the need to develop artificial intelligence systems, which is a large language model that should be trained using “correct” text samples that do not contain signs of disinformation, infodemic and unreliability. …”
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Possibilities and limitations of applying ChatGPT in the educational process by Namesztovszk Zsolt B., Glušac Dragana R., Arsović Branka B., Kovacs Elvira I.

“…One such technology is ChatGPT, a powerful large language model developed by OpenAI. In this paper, the authors consider the possibilities and limitations of applying artificial intelligence, primarily ChatGPT, in the educational process. …”
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An interactive address matching method based on a graph attention mechanism by Ming Li, Jialin Su, Zhiyu Song, Juping Qiu, Yongping Lin

“…Conclusion:: IAMGAM demonstrates excellent performance in Chinese address matching tasks, and the Large Language Model (LLM)-based methods, such as ChatGLM2-6B, show great potential for future development in this area.…”
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The PDC30 Chatbot—Development of a Psychoeducational Resource on Dementia Caregiving Among Family Caregivers: Mixed Methods Acceptability Study by Sheung-Tak Cheng, Peter H F Ng

“…MethodsThe PDC30 Chatbot was developed using the GPT-4o large language model, with a personality agent to constrain its behavior to provide advice on dementia caregiving based on the Positive Dementia Caregiving in 30 Days Guidebook—a laypeople’s resource based on a validated training manual for dementia caregivers. …”
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Assessing the Adherence of ChatGPT Chatbots to Public Health Guidelines for Smoking Cessation: Content Analysis by Lorien C Abroms, Artin Yousefi, Christina N Wysota, Tien-Chin Wu, David A Broniatowski

“… BackgroundLarge language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. …”
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Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review by Dmitry A Scherbakov, Nina C Hubig, Leslie A Lenert, Alexander V Alekseyenko, Jihad S Obeid

“…The screening and extraction process took place in Covidence with the help of a custom large language model (LLM) module developed by our team. …”
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Exploring artificial intelligence-powered virtual assistants to understand their potential to support older adults’ search needs by Emily M. Langston, Varitnan Hattakitjamroen, Mario Hernandez, Hye Soo Lee, Hannah Ç. Mason, Willencia Louis-Charles, Neil Charness, Sara J. Czaja, Wendy A. Rogers, Joseph Sharit, Walter R. Boot

“…Results: Overall, Large Language Model (LLM)-based virtual assistants (Bard, ChatGPT-4) responded more accurately than non-LLM assistants (e.g., 6 % inaccurate responses for Bard vs. 60 % for Alexa) and provided substantially more supplemental information (79 % of responses with high supplemental information for Bard and 37 % for Chat-GPT, vs. 20 % or less for others). …”
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