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1st Edition

LLMs Introduction, Background, Applications, Challenges, Limitations and Future Scope

Edited By Amit Kumar Tyagi Copyright 2027

446 Pages 120 B/W Illustrations

by CRC Press

Description

In today’s era, Large Language Models (LLMs) are advanced AI systems that are trained on large amounts of text data, to understand and generate human-like language. These systems built on transformer architectures have evolved from traditional NLP (Natural Language Processing) models to powerful tools that enable tasks like translation, summarization, coding, and conversational agents, etc., to... Read more

Table of Contents

Preface to the Series

Preface

Acknowledgement

Large Language Models (LLMs): Foundation and Architectures

Sanjana Sundar, S. Vinila Jinny, Jabanjalin Hilda and Shekina Justin

Core Components and Architectures of LLMs

Nisha Rathore, Manjushree Nayak, Shikha Tiwari and Syed Danish Hassan

Large Language Models (LLMs) in Aerospace: Use Cases and Applications

Vineet Bhatia, Sumati Sidharth and Bhavesh Bhatia

Large Language Models in Agriculture: Applications, Challenges, and Future Directions

Ritika and Savita Kumari Sheoran

The Rise of Transformer Architecture and Deep Learning in NLP

Shikha Tiwari, Nisha Rathore, Manjushree Nayak and Syed Danish Hassan

Integration of LLMs with Multimodal AI Systems

Rajalakshmi Nagarnaidu Rajaperumal

Next-Generation Virtual Assistants Powered by Multi-Modal Retrieval-Augmented Generation

Suvarna Patil, Sneha Kanawade, Nilima Dongre, Pooja Mishra, Priya Charles and Ketaki Bhoyar

Large Language Models for Text Generation: Foundations, Architectures, Applications, and Social Impacts

R. Satheesh Kumar, G. Keerthana, Ashwathy Anda Chacko, B. Reshmi and C. S. Sandeep

Fault Detection and Localization at Network Edges Using Lightweight Machine Learning Models

M. Rajesh, Vengatesan Krishnasamy and Sayyad Samee

Enterprise Applications: Automation, Analytics, and Knowledge Management

Maranco Murugaiyan, K. Balasubramanian, M. Sivakumar and P. Savaridassan

Leveraging Large Language Models for Fraud Detection and Risk Assessment in Financial Institutions—A Comprehensive Review

Aashka Thakkar, Axita Thakkar and Habtamu Ditta Hirpo

The Fusion of Quantum Intelligence and Large Language Models for Future Smart Healthcare

Amit Kumar Tyagi

Large Language Models in Industry 5.0: Fundamental and Applications

Aditya Pravinkumar Chaurasia, Meghna Manoj Nair and Amit Kumar Tyagi

Evaluation Metrics and Benchmarks for LLM Performance

R. Felista Sugirtha Lizy and I. Gusti Bagus Yosia Wiryakusuma

Challenges and Limitations in LLMs

K. Subbulakshmi and V. Karthikeyan

A New Framework for Bibliometric Network Analysis: Methodology, Implementation, and Case Study

K. Deeba, J. D. Dorathi Jayaseeli, R. Brindha, P. Renukadevi, Ajanthaa Lakkshmanan and R. Brindha

Deep Bibliometrics: Integrating Machine Learning for Enhanced Citation and Co-Authorship Analysis

Ajanthaa Lakkshmanan, R. Brindha, Sibi Amaran, Vanusha, R. Brindha and P. Renukadevi

Generating Question Answer-Pairs from a Given Set of Educational Text Using Transformer-Based Models

S. Shruthi and A. Vijayalakshmi

Index

Editor(s)

Biography

Amit Kumar Tyagi is working as an Assistant Professor, at National Forensic Sciences University, Gandhinagar, Gujarat, India. He received his Ph.D. Degree (Full-Time) in 2018 from Pondicherry Central University, India. Regarding his academic experience, he has worked as an assistant professor at several institutes like Lord Krishna College of Engineering (LKCE), Ghaziabad (for the periods of July 2009–July 2010, and October 2012–October 2013), Lingaya’s Vidyapeeth (formerly known as Lingaya’s University), Faridabad (September 2018–May 2019), VIT Chennai (June 2019–November 2022) and NIFT New Delhi (November 2022–September 2025). His current research focuses on Next Generation Machine Based Communications, Blockchain Technology, Smart and Secure Computing and Privacy. He is also a senior member of IEEE.

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