25 citations · 39 across the 7 of their papers we have counts for
7 papers
Understanding Secret Leakage Risks in Code LLMs: A Tokenization Perspective
Meifang Chen, Zhe Yang, Huang Nianchen +4
Code secrets are sensitive assets for software developers, and their leakage poses significant cybersecurity risks. While the rapid development of AI code assistants powered by Cod…
Data Compressibility Quantifies LLM Memorization
Yizhan Huang, Zhe Yang, Meifang Chen +3
Large Language Models (LLMs) are known to memorize portions of their training data, sometimes even reproduce content verbatim when prompted appropriately. Despite substantial inter…
Your Code Secret Belongs to Me: Neural Code Completion Tools Can Memorize Hard-Coded Credentials
Yizhan Huang, Yichen Li, Weibin Wu +2
Neural Code Completion Tools (NCCTs) have reshaped the field of software engineering, which are built upon the language modeling technique and can accurately suggest contextually r…
Transferable Adversarial Attacks on Vision Transformers with Token Gradient Regularization
Jianping Zhang, Yizhan Huang, Weibin Wu +1
Vision transformers (ViTs) have been successfully deployed in a variety of computer vision tasks, but they are still vulnerable to adversarial samples. Transfer-based attacks use a…
MTTM: Metamorphic Testing for Textual Content Moderation Software
Wenxuan Wang, Jen-tse Huang, Weibin Wu +5
The exponential growth of social media platforms such as Twitter and Facebook has revolutionized textual communication and textual content publication in human society. However, th…
Local Low-light Image Enhancement via Region-Aware Normalization
Shihurong Yao, Yizhan Huang, Xiaogang Xu
In the realm of Low-Light Image Enhancement (LLIE), existing research primarily focuses on enhancing images globally. However, many applications require local LLIE, where users are…
Improving Adversarial Transferability via Neuron Attribution-Based Attacks
Jianping Zhang, Weibin Wu, Jen-tse Huang +4
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples. It is thus imperative to devise effective attack algorithms to identify the deficiencies of DNNs bef…