31 papers
FinHardBench: Can LLMs Generate Latency-Aware Hardware for Financial Computing?
Weimin Fu, Hejia Zhang, Minghao Shao +6
Can large language models generate not just correct, but fast hardware? This paper investigates the question in financial FPGA design, where 5-10 nanoseconds of latency determines…
TrojanGYM: A Detector-in-the-Loop LLM for Adaptive RTL Hardware Trojan Insertion
Saideep Sreekumar, Zeng Wang, Akashdeep Saha +6
Hardware Trojans (HTs) remain a critical threat because learning-based detectors often overfit to narrow trigger/payload patterns and small, stylized benchmarks. We introduce Troja…
VHDLSuite: Unified Pipeline for LLM VHDL Generation with Data Synthesis and Evaluation
Yijun Shen, Minghao Shao, Yichen Zhao +4
Large Language Models (LLM) have shown impressive capabilities in Register Transfer Level (RTL) code generation, particularly for Verilog. However, evaluating their performance wit…
RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs
Parteek Jamwal, Minghao Shao, Boyuan Chen +15
Large Language Models (LLMs) have demonstrated remarkable capabilities across various cybersecurity tasks, including vulnerability classification, detection, and patching. However,…
QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy
Pasindu Wickramasinghe, Achyuta Muthuvelan, Rachmad Vidya Wicaksana Putra +2
LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus making them difficult to deploy on…
PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation
Minghao Shao, Nouhaila Innan, Hariharan Janardhanan +3
The growing complexity of quantum programming frameworks has exposed a critical limitation in existing large language model (LLM)-based code assistants: general-purpose models hall…