5 citations · 16 across the 14 of their papers we have counts for
19 papers
LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
Mohamad Fakih, Rahul Dharmaji, Halima Bouzidi +3
Software vulnerabilities continue to be ubiquitous, even in the era of AI-powered code assistants, advanced static analysis tools, and the adoption of extensive testing frameworks.…
Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition
Junyao Wang, Mohammad Abdullah Al Faruque
Deep learning has been widely adopted for human activity recognition (HAR) while generalizing a trained model across diverse users and scenarios remains challenging due to distribu…
Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception
Mohanad Odema, Luke Chen, Hyoukjun Kwon +1
We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems…
SMORE: Similarity-based Hyperdimensional Domain Adaptation for Multi-Sensor Time Series Classification
Junyao Wang, Mohammad Abdullah Al Faruque
Many real-world applications of the Internet of Things (IoT) employ machine learning (ML) algorithms to analyze time series information collected by interconnected sensors. However…
LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems
Mohamad Fakih, Rahul Dharmaji, Yasamin Moghaddas +3
Although Large Language Models (LLMs) have established pre-dominance in automated code generation, they are not devoid of shortcomings. The pertinent issues primarily relate to the…
Robust and Scalable Hyperdimensional Computing With Brain-Like Neural Adaptations
Junyao Wang, Mohammad Abdullah Al Faruque
The Internet of Things (IoT) has facilitated many applications utilizing edge-based machine learning (ML) methods to analyze locally collected data. Unfortunately, popular ML algor…