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Machine Learning algorithms have had a profound impact on the field of computer science over the past few decades. These algorithms performance is greatly influenced by the representations that are derived from the data in the learning…

The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language processing and moving towards multi-modal functionality.…

This paper provides a primer on Large Language Models (LLMs) and identifies their strengths, limitations, applications and research directions. It is intended to be useful to those in academia and industry who are interested in gaining an…

Computation and Language · Computer Science 2024-12-09 Sandra Johnson , David Hyland-Wood

Large language models (LLMs) are increasingly being deployed across disciplines due to their advanced reasoning and problem solving capabilities. To measure their effectiveness, various benchmarks have been developed that measure aspects of…

The paper presents an approach to build a question and answer system that is capable of processing the information in a large dataset and allows the user to gain knowledge from this dataset by asking questions in natural language form. Key…

Computation and Language · Computer Science 2019-02-07 M. R , Akram , C. P , Singhabahu , M. S. M Saad , P , Deleepa , Anupiya , Nugaliyadde , Yashas , Mallawarachchi

Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs on resource-constrained edge devices presents significant…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-25 Yue Zheng , Yuhao Chen , Bin Qian , Xiufang Shi , Yuanchao Shu , Jiming Chen

This comprehensive review explores the intersection of Large Language Models (LLMs) and cognitive science, examining similarities and differences between LLMs and human cognitive processes. We analyze methods for evaluating LLMs cognitive…

Artificial intelligence (AI) has demonstrated significant potential in transforming healthcare through the analysis and modeling of electronic health records (EHRs). However, the inherent heterogeneity, temporal irregularity, and…

Machine Learning · Computer Science 2025-07-18 Weijieying Ren , Jingxi Zhu , Zehao Liu , Tianxiang Zhao , Vasant Honavar

Integration of artificial intelligence (AI) into life cycle assessment (LCA) has accelerated in recent years, with numerous studies successfully adapting machine learning algorithms to support various stages of LCA. Despite this rapid…

Artificial Intelligence · Computer Science 2026-02-27 Anastasija Mensikova , Donna M. Rizzo , Kathryn Hinkelman

Large Language Models (LLMs) are being integrated into professional domains, yet their limitations in such high-stakes fields as law remain poorly understood. In response, this paper introduces examples of critical challenges to the…

Artificial Intelligence · Computer Science 2026-01-27 Eljas Linna , Tuula Linna

The rapid advancement of large language models (LLMs) has revolutionized artificial intelligence, introducing unprecedented capabilities in natural language processing and multimodal content generation. However, the increasing complexity…

Software Engineering · Computer Science 2024-11-27 Shenao Wang , Yanjie Zhao , Xinyi Hou , Haoyu Wang

As full AI-based automation remains out of reach in most real-world applications, the focus has instead shifted to leveraging the strengths of both human and AI agents, creating effective collaborative systems. The rapid advances in this…

Human-Computer Interaction · Computer Science 2024-04-19 Steffen Holter , Mennatallah El-Assady

Large language models are deep learning models with a large number of parameters. The models made noticeable progress on a large number of tasks, and as a consequence allowing them to serve as valuable and versatile tools for a diverse…

Software Engineering · Computer Science 2023-04-11 Maxim Vidgof , Stefan Bachhofner , Jan Mendling

Large Language Models (LLMs) have demonstrated remarkable language understanding and generation capabilities. However, training, deploying, and accessing these models pose notable challenges, including resource-intensive demands, extended…

Computation and Language · Computer Science 2024-01-31 Souvika Sarkar , Mohammad Fakhruddin Babar , Monowar Hasan , Shubhra Kanti Karmaker

Artificial Intelligence (AI) provides many opportunities to improve private and public life. Discovering patterns and structures in large troves of data in an automated manner is a core component of data science, and currently drives…

Artificial Intelligence · Computer Science 2019-10-11 Vaishak Belle

This research critically navigates the intricate landscape of AI deception, concentrating on deceptive behaviours of Large Language Models (LLMs). My objective is to elucidate this issue, examine the discourse surrounding it, and…

Computation and Language · Computer Science 2024-03-18 Linge Guo

While many researchers use Large Language Models (LLMs) through chat-based access, their real potential lies in leveraging LLMs via application programming interfaces (APIs). This paper conceptualizes LLMs as universal text processing…

Computation and Language · Computer Science 2026-03-23 Ivan Zupic

The rapid development of artificial intelligence has led to marked progress in the field. One interesting direction for research is whether Large Language Models (LLMs) can be integrated with structured knowledge-based systems. This…

Computation and Language · Computer Science 2025-05-02 Wenli Yang , Lilian Some , Michael Bain , Byeong Kang

Large language models (LLM) are advanced AI systems trained on extensive textual data, leveraging deep learning techniques to understand and generate human-like language. Today's LLMs with billions of parameters are so huge that hardly any…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-14 Sheikh Azizul Hakim , Saem Hasan

This chapter introduces the AI & Data Acumen Learning Outcomes Framework, a comprehensive tool designed to guide the integration of AI literacy across higher education. Developed through a collaborative process, the framework defines key AI…

Computers and Society · Computer Science 2025-10-30 Kathleen Kennedy , Anuj Gupta