Low-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources. by Muhammad Hussain, Caikou Chen, Sami S Albouq, Khlood Shinan, Fatmah Alanazi, Muhammad Waseem Iqbal, M Usman Ashraf

“…Our approach shows its potential to deliver competitive performance under limited resource constraints, comparable to large language models.…”
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Documenting Geographically and Contextually Diverse Language Data Sources by Angelina McMillan-Major, Francesco De Toni, Zaid Alyafeai, Stella Biderman, Kimbo Chen, Gérard Dupont, Hady Elsahar, Chris Emezue, Alham Fikri Aji, Suzana Ilić, Nurulaqilla Khamis, Colin Leong, Maraim Masoud, Aitor Soroa, Pedro Ortiz Suarez, Daniel van Strien, Zeerak Talat, Yacine Jernite

“… Contemporary large-scale data collection efforts have prioritized the amount of data collected to improve large language models (LLM). This quantitative approach has resulted in concerns for the rights of data subjects represented in data collections. …”
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AI Methods for Antimicrobial Peptides: Progress and Challenges by Carlos A. Brizuela, Gary Liu, Jonathan M. Stokes, Cesar de laFuente‐Nunez

“…Despite significant contributions, existing reviews have not thoroughly explored the potential of large language models (LLMs), graph neural networks (GNNs) and structure‐guided AMP discovery and design. …”
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Exploring the Role of AI-Based Conversational Agents for Collaborative Learning of English as a Foreign Language by Ebru Pınar Elmacı Er, Armin Weinberger

“…This paper investigates the evolving role of chat agents based on Artificial Intelligence (AI) and Large Language Models (LLM), notably ChatGPT, in the landscape of CL specific to EFL. …”
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The Machine as an Autonomous Explanatory Agent by Dilek Yargan

“…The prowess of Large Language Models (LLMs) serves as evidence: they enable seamless natural language communication and widespread use across various fields by swiftly processing unstructured data and handling diverse datasets with agility. …”
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CuTCP: Custom Text Generation-based Class-aware Prompt Tuning for visual-language models by Min Huang, Chen Yang, Xiaoyan Yu

“…CuTCP leverages large language models to generate descriptive, category-specific prompts, embedding richer semantic information that enhances the model’s ability to differentiate between known and unseen categories. …”
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CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking by Hansi Hettiarachchi, Amna Dridi, Mohamed Medhat Gaber, Pouyan Parsafard, Nicoleta Bocaneala, Katja Breitenfelder, Gonçal Costa, Maria Hedblom, Mihaela Juganaru-Mathieu, Thamer Mecharnia, Sumee Park, He Tan, Abdel-Rahman H. Tawil, Edlira Vakaj

“…It enables applying recent trends, such as deep neural networks and large language models, to ACC.…”
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Incremental accumulation of linguistic context in artificial and biological neural networks by Refael Tikochinski, Ariel Goldstein, Yoav Meiri, Uri Hasson, Roi Reichart

“…Abstract Large Language Models (LLMs) have shown success in predicting neural signals associated with narrative processing, but their approach to integrating context over large timescales differs fundamentally from that of the human brain. …”
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Clinical entity augmented retrieval for clinical information extraction by Ivan Lopez, Akshay Swaminathan, Karthik Vedula, Sanjana Narayanan, Fateme Nateghi Haredasht, Stephen P. Ma, April S. Liang, Steven Tate, Manoj Maddali, Robert Joseph Gallo, Nigam H. Shah, Jonathan H. Chen

“…Abstract Large language models (LLMs) with retrieval-augmented generation (RAG) have improved information extraction over previous methods, yet their reliance on embeddings often leads to inefficient retrieval. …”
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AI language model rivals expert ethicist in perceived moral expertise by Danica Dillion, Debanjan Mondal, Niket Tandon, Kurt Gray

“…Recent work suggests that large language models (LLMs) perform well on tasks designed to assess moral alignment, reflecting moral judgments with relatively high accuracy. …”
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Mapping the Green Urban: A Comprehensive Review of Materials and Learning Methods for Green Infrastructure Mapping by Dino Dobrinić, Mario Miler, Damir Medak

“…., screening) by using natural language processing and large language models. In total, this review analyzed 55 papers that included keywords related to GI mapping and provided materials and learning methods (i.e., machine or deep learning) essential for effective green infrastructure mapping. …”
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The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models. by Ahmed Daoud, Asa Ben-Hur

“…Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources. …”
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Language writ large: LLMs, ChatGPT, meaning, and understanding by Stevan Harnad

“…Apart from what (little) OpenAI may be concealing from us, we all know (roughly) how Large Language Models (LLMs) such as ChatGPT work (their vast text databases, statistics, vector representations, and huge number of parameters, next-word training, etc.). …”
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Unsupervised Text Embedding Space Generation Using Generative Adversarial Networks for Text Synthesis by Jun-Min Lee, Tae-Bin Ha

“…We expect to see extended research combining Large Language Models with a new perspective of viewing text as an continuous space.…”
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Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering by P. Banerjee, Anurag K. Srivastava, Donald A. Adjeroh, Ramana Reddy, Nima Karimian

“…Large Language Models (LLMs) like ChatGPT have become the most popular regenerative AI applications, used for obtaining responses for queries in different domains. …”
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AI for chemistry teaching: responsible AI and ethical considerations by Blonder Ron, Feldman-Maggor Yael

“…GenAI, driven by advanced AI models like Large Language Models, has shown substantial potential in generating educational content. …”
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Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies by Hae Sun Jung, Jang Hyun Kim, Haein Lee

“…The swift development of artificial intelligence (AI) technology has triggered substantial changes, particularly evident in the emergence of chat-based services driven by large language models. With the increasing number of users utilizing these services, understanding and analysing user satisfaction becomes crucial for service improvement. …”
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LLM-based collaborative programming: impact on students’ computational thinking and self-efficacy by Yi-Miao Yan, Chuang-Qi Chen, Yang-Bang Hu, Xin-Dong Ye

“…To address these challenges, Large Language Models (LLMs) can be introduced as a supportive tool to enhance both the efficiency and outcomes of collaborative programming. …”
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ChatGPT and oral cancer: a study on informational reliability by Mesude Çi̇ti̇r

“…Abstract Background Artificial intelligence (AI) and large language models (LLMs) like ChatGPT have transformed information retrieval, including in healthcare. …”
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LLM-AIDSim: LLM-Enhanced Agent-Based Influence Diffusion Simulation in Social Networks by Lan Zhang, Yuxuan Hu, Weihua Li, Quan Bai, Parma Nand

“…This paper introduces an LLM-Enhanced Agent-Based Influence Diffusion Simulation (LLM-AIDSim) framework that integrates large language models (LLMs) into agent-based modelling to simulate influence diffusion in social networks. …”
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