37 citations · 66 across the 9 of their papers we have counts for
10 papers
Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers
Harri Renney, Fouad Trad, Michael Mattarock +2
Large language models (LLMs) are becoming increasingly capable at small parameter scales. At the same time, conventional cloud-centric deployment introduces challenges around data…
Chained Prompting for Better Systematic Review Search Strategies
Fatima Nasser, Fouad Trad, Ammar Mohanna +2
Systematic reviews require the use of rigorously designed search strategies to ensure both comprehensive retrieval and minimization of bias. Conventional manual approaches, althoug…
Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection
Fouad Trad, Ali Chehab
Few-shot prompting has emerged as a practical alternative to fine-tuning for leveraging the capabilities of large language models (LLMs) in specialized tasks. However, its effectiv…
CLASP: Cost-Optimized LLM-based Agentic System for Phishing Detection
Fouad Trad, Ali Chehab
Phishing websites remain a significant cybersecurity threat, necessitating accurate and cost-effective detection mechanisms. In this paper, we present CLASP, a novel system that ef…
Detecting Quishing Attacks with Machine Learning Techniques Through QR Code Analysis
Fouad Trad, Ali Chehab
The rise of QR code-based phishing ("Quishing") poses a growing cybersecurity threat, as attackers increasingly exploit QR codes to bypass traditional phishing defenses. Existing d…
Streamlining Systematic Reviews: A Novel Application of Large Language Models
Fouad Trad, Ryan Yammine, Jana Charafeddine +4
Systematic reviews (SRs) are essential for evidence-based guidelines but are often limited by the time-consuming nature of literature screening. We propose and evaluate an in-house…
Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction
Fouad Trad, Ali Chehab
With the rise of sophisticated phishing attacks, there is a growing need for effective and economical detection solutions. This paper explores the use of large multimodal agents, s…
To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models
Fouad Trad, Ali Chehab
The effectiveness of Large Language Models (LLMs) significantly relies on the quality of the prompts they receive. However, even when processing identical prompts, LLMs can yield v…
Evaluating the Efficacy of Prompt-Engineered Large Multimodal Models Versus Fine-Tuned Vision Transformers in Image-Based Security Applications
Fouad Trad, Ali Chehab
The success of Large Language Models (LLMs) has led to a parallel rise in the development of Large Multimodal Models (LMMs), which have begun to transform a variety of applications…
Forecast Analysis of the COVID-19 Incidence in Lebanon: Prediction of Future Epidemiological Trends to Plan More Effective Control Programs
Salah El Falou, Fouad Trad
Ever since the COVID-19 pandemic started, all the governments have been trying to limit its effects on their citizens and countries. This pandemic was harsh on different levels for…