12 citations · 101 across the 80 of their papers we have counts for
22 papers · 1 filter
Data-Free Hard-Label Robustness Stealing Attack
Xiaojian Yuan, Kejiang Chen, Wen Huang +3
The popularity of Machine Learning as a Service (MLaaS) has led to increased concerns about Model Stealing Attacks (MSA), which aim to craft a clone model by querying MLaaS. Curren…
Controlling risks of AI in chemical science with agents
Jiyan He, Weitao Feng, Haoxiang Guan +11
Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substances, or circumvention of establ…
Detecting Voice Cloning Attacks via Timbre Watermarking
Chang Liu, Jie Zhang, Tianwei Zhang +3
Nowadays, it is common to release audio content to the public. However, with the rise of voice cloning technology, attackers have the potential to easily impersonate a specific per…
Silent Guardian: Protecting Text from Malicious Exploitation by Large Language Models
Jiawei Zhao, Kejiang Chen, Xiaojian Yuan +3
The rapid development of large language models (LLMs) has yielded impressive success in various downstream tasks. However, the vast potential and remarkable capabilities of LLMs al…
Performance-lossless Black-box Model Watermarking
Na Zhao, Kejiang Chen, Weiming Zhang +1
With the development of deep learning, high-value and high-cost models have become valuable assets, and related intellectual property protection technologies have become a hot topi…
OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation
Qidong Huang, Xiaoyi Dong, Pan Zhang +6
Hallucination, posed as a pervasive challenge of multi-modal large language models (MLLMs), has significantly impeded their real-world usage that demands precise judgment. Existing…
CMFDFormer: Transformer-based Copy-Move Forgery Detection with Continual Learning
Yaqi Liu, Chao Xia, Song Xiao +4
Copy-move forgery detection aims at detecting duplicated regions in a suspected forged image, and deep learning based copy-move forgery detection methods are in the ascendant. Thes…
Turning Your Strength into Watermark: Watermarking Large Language Model via Knowledge Injection
Shuai Li, Kejiang Chen, Kunsheng Tang +4
Large language models (LLMs) have demonstrated outstanding performance, making them valuable digital assets with significant commercial potential. Unfortunately, the LLM and its AP…
Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World
Zhiling Zhang, Jie Zhang, Kui Zhang +3
The widespread use of face recognition technology has given rise to privacy concerns, as many individuals are worried about the collection and utilization of their facial data. To…
HairCLIPv2: Unifying Hair Editing via Proxy Feature Blending
Tianyi Wei, Dongdong Chen, Wenbo Zhou +4
Hair editing has made tremendous progress in recent years. Early hair editing methods use well-drawn sketches or masks to specify the editing conditions. Even though they can enabl…
InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model
Meng Tong, Kejiang Chen, Jie Zhang +5
Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unau…
Catch You Everything Everywhere: Guarding Textual Inversion via Concept Watermarking
Weitao Feng, Jiyan He, Jie Zhang +4
AIGC (AI-Generated Content) has achieved tremendous success in many applications such as text-to-image tasks, where the model can generate high-quality images with diverse prompts,…
Aparecium: Revealing Secrets from Physical Photographs
Zhe Lei, Jie Zhang, Jingtao Li +2
Watermarking is a crucial tool for safeguarding copyrights and can serve as a more aesthetically pleasing alternative to QR codes. In recent years, watermarking methods based on de…
Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting
Qidong Huang, Xiaoyi Dong, Dongdong Chen +5
In this paper, we investigate the adversarial robustness of vision transformers that are equipped with BERT pretraining (e.g., BEiT, MAE). A surprising observation is that MAE has…
Watermarking Text Generated by Black-Box Language Models
Xi Yang, Kejiang Chen, Weiming Zhang +5
LLMs now exhibit human-like skills in various fields, leading to worries about misuse. Thus, detecting generated text is crucial. However, passive detection methods are stuck in do…
DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection
Xiao Yu, Yuang Qi, Kejiang Chen +6
Large language models (LLMs) have the potential to generate texts that pose risks of misuse, such as plagiarism, planting fake reviews on e-commerce platforms, or creating inflamma…
Deep Intellectual Property Protection: A Survey
Yuchen Sun, Tianpeng Liu, Panhe Hu +6
Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made revolutionary progress in recent years, and are widely used in various fields. The high performance of DNN…
Diversity-Aware Meta Visual Prompting
Qidong Huang, Xiaoyi Dong, Dongdong Chen +4
We present Diversity-Aware Meta Visual Prompting~(DAM-VP), an efficient and effective prompting method for transferring pre-trained models to downstream tasks with frozen backbone.…
ICStega: Image Captioning-based Semantically Controllable Linguistic Steganography
Xilong Wang, Yaofei Wang, Kejiang Chen +3
Nowadays, social media has become the preferred communication platform for web users but brought security threats. Linguistic steganography hides secret data into text and sends it…
Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network
Xiaojian Yuan, Kejiang Chen, Jie Zhang +3
Model inversion (MI) attacks have raised increasing concerns about privacy, which can reconstruct training data from public models. Indeed, MI attacks can be formalized as an optim…
OAcode: Overall Aesthetic 2D Barcode on Screen
Zehua Ma, Xi Yang, Han Fang +2
Nowadays, two-dimensional (2D) barcodes have been widely used in various domains. And a series of aesthetic 2D barcode schemes have been proposed to improve the visual quality and…
VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum
Huanyu Bian, Zhilong Jia, Menghan Dou +13
With the rapid development of classical and quantum machine learning, a large number of machine learning frameworks have been proposed. However, existing machine learning framework…