12 citations · 28 across the 35 of their papers we have counts for
8 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…
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…