2 citations · 2 across the 6 of their papers we have counts for
6 papers
ConQuER: Modular Architectures for Control and Bias Mitigation in IQP Quantum Generative Models
Xiaocheng Zou, Shijin Duan, Charles Fleming +4
Quantum generative models based on instantaneous quantum polynomial (IQP) circuits show great promise in learning complex distributions while maintaining classical trainability. Ho…
MetaSeal: Defending Against Image Attribution Forgery Through Content-Dependent Cryptographic Watermarks
Tong Zhou, Ruyi Ding, Gaowen Liu +5
The rapid growth of digital and AI-generated images has amplified the need for secure and verifiable methods of image attribution. While digital watermarking offers more robust pro…
ProDiF: Protecting Domain-Invariant Features to Secure Pre-Trained Models Against Extraction
Tong Zhou, Shijin Duan, Gaowen Liu +4
Pre-trained models are valuable intellectual property, capturing both domain-specific and domain-invariant features within their weight spaces. However, model extraction attacks th…
Towards Vector Optimization on Low-Dimensional Vector Symbolic Architecture
Shijin Duan, Yejia Liu, Gaowen Liu +3
Vector Symbolic Architecture (VSA) is emerging in machine learning due to its efficiency, but they are hindered by issues of hyperdimensionality and accuracy. As a promising mitiga…
Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature
Tong Zhou, Xuandong Zhao, Xiaolin Xu +1
Text watermarks for large language models (LLMs) have been commonly used to identify the origins of machine-generated content, which is promising for assessing liability when comba…
Scheduled Knowledge Acquisition on Lightweight Vector Symbolic Architectures for Brain-Computer Interfaces
Yejia Liu, Shijin Duan, Xiaolin Xu +1
Brain-Computer interfaces (BCIs) are typically designed to be lightweight and responsive in real-time to provide users timely feedback. Classical feature engineering is computation…