2 citations · 2 across the 11 of their papers we have counts for
11 papers
Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition
Yifan Liao, Zongmin Zhang, Zhen Sun +3
Automatic speech recognition (ASR) systems have become widely used for multilingual speech-to-text transcription. Their robustness to adversarial attacks has become an important to…
Escaping the Linearity Trap: Manifold Detours for Black-Box Adversarial Attacks on Singing Audio Deepfake Detection
Yifan Liao, Yule Liu, Zhen Sun +5
Recent Singing Voice Synthesis (SVS) advances enable highly realistic but potentially malicious AI covers, making singing voice deepfake detection (SVDD) crucial. Self-Supervised L…
Stego Battlefield: Evaluating Image Steganography Attacks and Steganalysis Defenses
Zhen Sun, Zongmin Zhang, Leyi Sheng +7
Image steganography is widely used to protect user privacy and enable covert communication. However, it can also be abused by the adversary as a covert channel to bypass content mo…
CHASM: Unveiling Covert Advertisements on Chinese Social Media
Jingyi Zheng, Tianyi Hu, Yule Liu +5
Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements, which disguise themselves as…
IPV-Bench: Benchmarking Image Protection Methods under Diverse Image-to-Video Generation Scenarios
Xiaofeng Li, Leyi Sheng, Yifan Zhao +4
Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image protection methods that aim to dis…
6DAttack: Backdoor Attacks in the 6DoF Pose Estimation
Jihui Guo, Zongmin Zhang, Zhen Sun +4
Deep learning advances have enabled accurate six-degree-of-freedom (6DoF) object pose estimation, widely used in robotics, AR/VR, and autonomous systems. However, backdoor attacks…
Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models
Zongmin Zhang, Zhen Sun, Yifan Liao +5
Prompt-driven Video Segmentation Foundation Models (VSFMs), such as SAM2, are increasingly used in applications including autonomous driving and digital pathology, yet their securi…
"To Survive, I Must Defect": Jailbreaking LLMs via the Game-Theory Scenarios
Zhen Sun, Zongmin Zhang, Deqi Liang +8
As LLMs become more common, non-expert users can pose risks, prompting extensive research into jailbreak attacks. However, most existing black-box jailbreak attacks rely on hand-cr…
SynDec: A Synthesize-then-Decode Approach for Arbitrary Textual Style Transfer via Large Language Models
Han Sun, Zhen Sun, Zongmin Zhang +3
Large Language Models (LLMs) are emerging as dominant forces for textual style transfer. However, for arbitrary style transfer, LLMs face two key challenges: (1) considerable relia…
Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applications
Wenhan Dong, Yuemeng Zhao, Zhen Sun +10
As large language models (LLMs) are increasingly used in human-centered tasks, assessing their psychological traits is crucial for understanding their social impact and ensuring tr…
Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media
Zhen Sun, Zongmin Zhang, Xinyue Shen +5
Social media platforms are experiencing a growing presence of AI-Generated Texts (AIGTs). However, the misuse of AIGTs could have profound implications for public opinion, such as…