Academic Articles & Research Papers

Interaction with LLM-Based Systems: A Structured Review and Taxonomy of Mechanisms and Autonomy

Large language models (LLMs) are increasingly integrated into interactive systems across domains such as software development, robotics, and education. As these systems evolve from simple chat interfaces to autonomous, tool-using agents, th...

Synergizing Generative AI and Cybersecurity: Roles of Generative AI Entities, Companies, Agencies, and Government in Enhancing Cybersecurity

The digital landscape of the modern world has witnessed a remarkable evolution over the past few decades, with technological advancements permeating every facet of our lives. While these innovations have brought forth unprecedented convenie...

Review of Generative AI methods in cybersecurity

Over the last decade, Artificial Intelligence (AI) has become increasingly popular, especially with the use of chatbots such as ChatGPT, Google’s Gemini, and DALL-E. With this rise, large language models (LLMs) and Generative AI (GenAI) hav...

Generative AI in cybersecurity: A comprehensive review of LLM applications and vulnerabilities

This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection, s...

Large Language Models in Cybersecurity: State-of-the-Art

The rise of Large Language Models (LLMs) has revolutionized our comprehension of intelligence bringing us closer to Artificial Intelligence. Since their introduction, researchers have actively explored the applications of LLMs across divers...

Toward Autonomous Extraction and Building of Machine-Readable Molecular Models from Publications Using Large Language Models.

Enhancing Psychiatry Training Using an Agentic AI Simulated Consultation Tool: Prospective Cohort Study

Abstract BackgroundCanadian psychiatry residents must demonstrate consultation competency, assessed using the standardized assessment of a clinical encounter report (STACER). However, opportunities to practice these skills and r...

Integrating Adversarial Scenarios into LLM Security Labs: An Experience Report on a Hands-On Approach

This paper presents an exploratory case study detailed as a pedagogical experience report on integrating adversarial Large Language Model (LLM) scenarios into a graduate cybersecurity curriculum. In addition to prompt injection, sophisticat...

Sequence Decision Transformer for Adaptive Traffic Signal Control

Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement lear...

Quantifying Gender Bias in Large Language Models Using Information-Theoretic and Statistical Analysis

Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...

Applications of natural language processing and large language models in materials discovery

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

AI-generated draft replies to patient messages: exploring effects of implementation

IntroductionThe integration of Large Language Models (LLMs) in Electronic Health Records (EHRs) has the potential to reduce administrative burden. Validating these tools in real-world clinical settings is essential for responsible implement...

Construction of a knowledge graph for the educational statistical indicator system based on large language models

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN

Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream tasks. Despite their ...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies

Online platforms have become the primary means for travellers to search, compare, and book accommodations for their trips. Consequently, online platforms and revenue managers must acquire a comprehensive comprehension of these dynamics to f...

Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot-i.e., without adaptation on downstream data.Recently, the debut of ChatGP...

Prompting Strategies for Readability Alignment Between User-Generated Ophthalmology Questions and Large Language Model Answers: Comparative Evaluation Study.

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

Machine Reading Comprehension for the Tamil Language With Translated SQuAD

Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...