26 citations · 64 across the 15 of their papers we have counts for
17 papers
Inference-time Alignment via Sparse Junction Steering
Runyi Hu, Jie Zhang, Shiqian Zhao +7
Token-level steering has emerged as a pivotal approach for inference-time alignment, enabling fine grained control over large language models by modulating their output distributio…
Mask Image Watermarking
Runyi Hu, Jie Zhang, Shiqian Zhao +5
We present MaskWM, a simple, efficient, and flexible framework for image watermarking. MaskWM has two variants: (1) MaskWM-D, which supports global watermark embedding, watermark l…
VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking
Runyi Hu, Jie Zhang, Yiming Li +4
Artificial Intelligence Generated Content (AIGC) has advanced significantly, particularly with the development of video generation models such as text-to-video (T2V) models and ima…
Picky LLMs and Unreliable RMs: An Empirical Study on Safety Alignment after Instruction Tuning
Guanlin Li, Kangjie Chen, Shangwei Guo +6
Large language models (LLMs) have emerged as powerful tools for addressing a wide range of general inquiries and tasks. Despite this, fine-tuning aligned LLMs on smaller, domain-sp…
SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution
Runyi Hu, Jie Zhang, Yiming Li +4
In today's digital landscape, the blending of AI-generated and authentic content has underscored the need for copyright protection and content authentication. Watermarking has beco…
Robust-Wide: Robust Watermarking against Instruction-driven Image Editing
Runyi Hu, Jie Zhang, Ting Xu +2
Instruction-driven image editing allows users to quickly edit an image according to text instructions in a forward pass. Nevertheless, malicious users can easily exploit this techn…
Rethinking Adversarial Training with Neural Tangent Kernel
Guanlin Li, Han Qiu, Shangwei Guo +2
Adversarial training (AT) is an important and attractive topic in deep learning security, exhibiting mysteries and odd properties. Recent studies of neural network training dynamic…
Warfare:Breaking the Watermark Protection of AI-Generated Content
Guanlin Li, Yifei Chen, Jie Zhang +5
AI-Generated Content (AIGC) is rapidly expanding, with services using advanced generative models to create realistic images and fluent text. Regulating such content is crucial to p…
SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View
Yuan Xu, Xingshuo Han, Gelei Deng +3
Robotic Vehicles (RVs) have gained great popularity over the past few years. Meanwhile, they are also demonstrated to be vulnerable to sensor spoofing attacks. Although a wealth of…
ShiftNAS: Towards Automatic Generation of Advanced Mulitplication-Less Neural Networks
Xiaoxuan Lou, Guowen Xu, Kangjie Chen +3
Multiplication-less neural networks significantly reduce the time and energy cost on the hardware platform, as the compute-intensive multiplications are replaced with lightweight b…
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving
Xingshuo Han, Guowen Xu, Yuan Zhou +3
Modern autonomous vehicles adopt state-of-the-art DNN models to interpret the sensor data and perceive the environment. However, DNN models are vulnerable to different types of adv…
Threats to Pre-trained Language Models: Survey and Taxonomy
Shangwei Guo, Chunlong Xie, Jiwei Li +2
Pre-trained language models (PTLMs) have achieved great success and remarkable performance over a wide range of natural language processing (NLP) tasks. However, there are also gro…
Protecting Your NLG Models with Semantic and Robust Watermarks
Tao Xiang, Chunlong Xie, Shangwei Guo +2
Natural language generation (NLG) applications have gained great popularity due to the powerful deep learning techniques and large training corpus. The deployed NLG models may be s…
Fingerprinting Multi-exit Deep Neural Network Models via Inference Time
Tian Dong, Han Qiu, Tianwei Zhang +3
Transforming large deep neural network (DNN) models into the multi-exit architectures can overcome the overthinking issue and distribute a large DNN model on resource-constrained s…
Fingerprinting Image-to-Image Generative Adversarial Networks
Guanlin Li, Guowen Xu, Han Qiu +5
Generative Adversarial Networks (GANs) have been widely used in various application scenarios. Since the production of a commercial GAN requires substantial computational and human…
Ownership Verification of DNN Architectures via Hardware Cache Side Channels
Xiaoxuan Lou, Shangwei Guo, Jiwei Li +1
Deep Neural Networks (DNN) are gaining higher commercial values in computer vision applications, e.g., image classification, video analytics, etc. This calls for urgent demands of…
IcoRating: A Deep-Learning System for Scam ICO Identification
Shuqing Bian, Zhenpeng Deng, Fei Li +9
Cryptocurrencies (or digital tokens, digital currencies, e.g., BTC, ETH, XRP, NEO) have been rapidly gaining ground in use, value, and understanding among the public, bringing asto…