3 citations · 3 across the 10 of their papers we have counts for
12 papers
Which Image Property Carries the Jailbreak? A Controlled Dissection of Image-to-Text Jailbreaks
Boyuan Chen, Yehia Dawoud, Hailemariam Mersha +4
Image-to-text jailbreaks place harmful intent in text, image content, or the relationship between them. We examine image-side factors across four published attack families on a 313…
Where Does the Audio Jailbreak Live? A Controlled Frequency-Depth Audit of AdvWave-P on Qwen2-Audio
Boyuan Chen, Minseok Kim, Sohaila Abdulsattar +4
We audit frequency and decoder-depth claims for AdvWave-P, an additive audio jailbreak, on Qwen2-Audio. The protocol masks frequency components of the perturbation in the short-tim…
Surgical Repair of Insecure Code Generation in LLMs
Gustavo Sandoval, Brendan Dolan-Gavitt, Siddharth Garg
Large language models write production code, and yet they routinely introduce well-known vulnerabilities. We show that this is not a knowledge deficit: the same models that generat…
VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation
Luca Collini, Andrew Hennesee, Patrick Yubeaton +2
Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between model characteristics and prompt design c…
AI In Cybersecurity Education -- Scalable Agentic CTF Design Principles and Educational Outcomes
Haoran Xi, Minghao Shao, Kimberly Milner +11
Large language models are rapidly changing how learners acquire and demonstrate cybersecurity skills. However, when human--AI collaboration is allowed, educators still lack validat…
Exploring the Agentic Frontier of Verilog Code Generation
Patrick Yubeaton, Siddharth Garg, Chinmay Hegde
Large language models (LLMs) have made rapid advancements in code generation for popular languages such as Python and C++. Many of these recent gains can be attributed to the use o…
GroundCount: Grounding Vision-Language Models with Object Detection for Mitigating Counting Hallucinations
Boyuan Chen, Minghao Shao, Siddharth Garg +2
Vision Language Models (VLMs) exhibit persistent hallucinations in counting tasks, with accuracy substantially lower than other visual reasoning tasks (excluding sentiment). This p…
TrojanLoC: LLM-based Framework for RTL Trojan Localization
Weihua Xiao, Zeng Wang, Minghao Shao +6
Hardware Trojans (HT s) are a persistent threat to integrated circuits, especially when inserted at the register-transfer level (RTL). Existing methods typically first convert the…
Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA
Weihua Xiao, Derek Ekberg, Siddharth Garg +1
SystemVerilog Assertions (SVAs) are critical for verifying the correctness of hardware designs, but manually writing them from natural language property descriptions, i.e., NL2SVA,…
MetaCipher: A Time-Persistent and Universal Multi-Agent Framework for Cipher-Based Jailbreak Attacks for LLMs
Boyuan Chen, Minghao Shao, Abdul Basit +2
As large language models (LLMs) grow more capable, they face growing vulnerability to sophisticated jailbreak attacks. While developers invest heavily in alignment finetuning and s…
NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security
Minghao Shao, Sofija Jancheska, Meet Udeshi +10
Large Language Models (LLMs) are being deployed across various domains today. However, their capacity to solve Capture the Flag (CTF) challenges in cybersecurity has not been thoro…
Model Cascading for Code: A Cascaded Black-Box Multi-Model Framework for Cost-Efficient Code Completion with Self-Testing
Boyuan Chen, Mingzhi Zhu, Brendan Dolan-Gavitt +2
The rapid advancement of large language models (LLMs) has significantly improved code completion tasks, yet the trade-off between accuracy and computational cost remains a critical…