collaborators

5 papers

cs.SE2026

Leveraging Large Language Models to Obscure Code Stylometry: A Comparative Study of GPT-3.5 and GPT-4

Saman Pordanesh, Benjamin Tan

In the rapidly evolving field of software development, code stylometry analyzing unique stylistic signatures of programmers plays a crit-ical role in authorship attribution and cyb…

cs.AR2026

PCB-QA: Evaluating LLMs over the First Printed Circuit Board Design Question-Answer Dataset

Sahana Srinivasan, Benjamin Tan, Benjamin Turnbull +1

Large Language Models (LLMs) have demonstrated capabilities in electronic design automation (EDA) for integrated circuits. However, their applications in printed circuit board (PCB…

cs.AR2025

Towards LLM-based Root Cause Analysis of Hardware Design Failures

Siyu Qiu, Muzhi Wang, Raheel Afsharmazayejani +3

With advances in large language models (LLMs), new opportunities have emerged to develop tools that support the digital hardware design process. In this work, we explore how LLMs c…

cs.CR2025

Large Language Models and Attention-Based AI for Hardware Design and Security: Progress, Challenges, and Opportunities

Sujan Ghimire, Parsa Mirfasihi, Muhtasim Alam Chowdhury +9

Recent advances in attention-based artificial intelligence (AI) models have unlocked vast potential to automate digital hardware design while enhancing and strengthening security m…

cs.CR2025

LASHED: LLMs And Static Hardware Analysis for Early Detection of RTL Bugs

Baleegh Ahmad, Hammond Pearce, Ramesh Karri +1

While static analysis is useful in detecting early-stage hardware security bugs, its efficacy is limited because it requires information to form checks and is often unable to expla…