Academic Articles & Research Papers

Year 2024: Trends towards Multi-[tasks, languages, models] and Large Adoption of LLMs.

Performance of Open-Source LLMs in Identifying Pediatric Pneumonia From Free-Text Chest Radiograph Reports.

Response to: Five methodological considerations for validating LLMs in risk of bias assessment.

Identifying practices for meaningful health research partnerships: series of rapid environmental scans.

From assistance to accountability: a systematic scoping review of LLMs in responsible scholarly review, research integrity, and scientometrics.

Comparative assessment of patient education content generated by five large language models on post-stroke complications: A cross-sectional study of safety, accuracy, reliability, readability, and empathy

Objective To compare the safety, accuracy, reliability, readability, and empathy of patient education content generated by five large language models (LLMs) for post-stroke complications. Methods This CHART-guided cross-sectional comparativ...

Evaluating an LLM-assisted workflow for clinical documentation: A pilot randomized controlled trial on time and quality.

Large language models (LLMs) have been investigated for clinical documentation, with concerns about hallucinations and factual errors. Clinician review and revision of LLM-generated drafts are considered essential; however, the impact of su...

Comparative Analysis of Deep Natural Networks and Large Language Models for Aspect-Based Sentiment Analysis

Sentiment analysis is essential for comprehending public opinion, particularly when considering e-commerce and the expansion of online businesses. Early approaches treated sentiment analysis as a document or sentence-level classification pr...

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...

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...

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. ...