14 citations · 36 across the 36 of their papers we have counts for
39 papers
ASCENT: First-Order Optimal Fine-Tuning with Recalibration for Safety--Utility Co-Enhancement
Weiwei Qi, Chongyu Wang, Tianhang Zheng +5
Supervised fine-tuning can substantially improve the downstream utility of large language models (LLMs) but may compromise their safety. Existing safety-preserving methods constrai…
Task-Aware Joint Pruning and Distillation for Efficient Audio Deepfake Detection
Miao He, Peng Cheng, Zhongjie Ba +4
Advances in speech synthesis have made deepfake speeches increasingly convincing, posing growing threats to security. While self-supervised learning (SSL) based detectors achieve s…
RAEGNet: Relation-Aware Evidence Graph Network for Harm-Aware Multimodal Fake News Detection
Wenbin Shen, Guoxuan Qin, Guangxu Yao +4
Existing multimodal fake news detection methods often introduce external information to assist detection. However, most of them rely on entity-level retrieval and are therefore pro…
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs
Zhongjie Ba, Shengwang Xu, Peng Cheng +4
Embodied intelligence and world models require video understanding systems to go beyond recognizing objects and actions and develop an understanding of physical regularities. Howev…
Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection
Haoyu Wang, Yiming Qin, Zhongjie Ba +4
AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated under image-free generation par…
MixFake: Benchmarking and Enhancing Audio Deepfake Detection in Diverse Real-world Mixed Audio
Qingcao Li, Yipeng Lin, Weichen Lian +3
Speech deepfake detection has achieved remarkable success in clean environments but faces significant challenges in complex, real-world scenarios where speech is often mixed with b…
Beyond Content: A Comprehensive Speech Toxicity Dataset and Detection Framework Incorporating Paralinguistic Cues
Zhongjie Ba, Liang Yi, Peng Cheng +3
Toxic speech detection has become a crucial challenge in maintaining safe online communication environments. However, existing approaches to toxic speech detection often neglect th…
"Training robust watermarking model may hurt authentication!'' Exploring and Mitigating the Identity Leakage in Robust Watermarking
Xinyu Zhang, Ziping Dong, Qingyu Liu +3
The rapid advancement of generative AI has underscored the critical need for identifying image ownership and protecting copyrights. This makes post-processing image watermarking an…
PromptForge-350k: A Large-Scale Dataset and Contrastive Framework for Prompt-Based AI Image Forgery Localization
Jianpeng Wang, Haoyu Wang, Baoying Chen +4
The rapid democratization of prompt-based AI image editing has recently exacerbated the risks associated with malicious content fabrication and misinformation. However, forgery loc…
When Detectors Forget Forensics: Blocking Semantic Shortcuts for Generalizable AI-Generated Image Detection
Chao Shuai, Shaojing Fan, Chenlin Zou +6
The growing realism of generative models has blurred the boundary between real and synthetic content, posing significant challenges to reliable AI-generated image detection. Althou…
HyperPotter: Spell the Charm of High-Order Interactions in Audio Deepfake Detection
Qing Wen, Haohao Li, Zhongjie Ba +4
Advances in AIGC technologies have enabled the synthesis of highly realistic audio deepfakes capable of deceiving human auditory perception. Although numerous audio deepfake detect…
RBD: A Reconstruction-Based Method for Generalizable and Efficient Detection of Fake Images
Qingyu Liu, Zhongjie Ba, Jianmin Guo +4
Recently, reconstruction-based methods have gained attention for AIGC image detection. These methods leverage pre-trained diffusion models to reconstruct inputs and measure residua…
Attack-Resistant Watermarking for AIGC Image Forensics via Diffusion-based Semantic Deflection
Qingyu Liu, Yitao Zhang, Zhongjie Ba +4
Protecting the copyright of user-generated AI images is an emerging challenge as AIGC becomes pervasive in creative workflows. Existing watermarking methods (1) remain vulnerable t…
AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security
Dongrui Liu, Qihan Ren, Chen Qian +40
The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current guardrail models lack agentic risk…
FBAD: Frequency-based Black-box Attack for AI-generated Image Detection
Xiaojing Chen, Dan Li, Lijun Peng +6
The prosperous development of Artificial Intelligence-Generated Content (AIGC) has brought people's anxiety about the spread of false information on social media. Designing detecto…
Are Your Agents Upward Deceivers?
Dadi Guo, Qingyu Liu, Dongrui Liu +13
Large Language Model (LLM)-based agents are increasingly used as autonomous subordinates that carry out tasks for users. This raises the question of whether they may also engage in…
MVAD: A Benchmark Dataset for Multimodal AI-Generated Video-Audio Detection
Mengxue Hu, Yunfeng Diao, Changtao Miao +7
The rapid advancement of AI-generated multimodal video-audio content has raised significant concerns regarding information security and content authenticity. Existing synthetic vid…
Model Discrepancy Learning: Synthetic Faces Detection Based on Multi-Reconstruction
Qingchao Jiang, Zhishuo Xu, Zhiying Zhu +3
Advances in image generation enable hyper-realistic synthetic faces but also pose risks, thus making synthetic face detection crucial. Previous research focuses on the general diff…
Harnessing Frequency Spectrum Insights for Image Copyright Protection Against Diffusion Models
Zhenguang Liu, Chao Shuai, Shaojing Fan +4
Diffusion models have achieved remarkable success in novel view synthesis, but their reliance on large, diverse, and often untraceable Web datasets has raised pressing concerns abo…
WMCopier: Forging Invisible Image Watermarks on Arbitrary Images
Ziping Dong, Chao Shuai, Zhongjie Ba +4
Invisible Image Watermarking is crucial for ensuring content provenance and accountability in generative AI. While Gen-AI providers are increasingly integrating invisible watermark…
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
Yu He, Boheng Li, Liu Liu +6
Membership Inference Attacks (MIAs) aim to predict whether a data sample belongs to the model's training set or not. Although prior research has extensively explored MIAs in Large…
Robust Watermarks Leak: Channel-Aware Feature Extraction Enables Adversarial Watermark Manipulation
Zhongjie Ba, Yitao Zhang, Peng Cheng +4
Watermarking plays a key role in the provenance and detection of AI-generated content. While existing methods prioritize robustness against real-world distortions (e.g., JPEG compr…
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
Gaojian Wang, Feng Lin, Tong Wu +3
This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable facial representation that boosts various face security tasks with respect to generaliza…
ALIF: Low-Cost Adversarial Audio Attacks on Black-Box Speech Platforms using Linguistic Features
Peng Cheng, Yuwei Wang, Peng Huang +5
Extensive research has revealed that adversarial examples (AE) pose a significant threat to voice-controllable smart devices. Recent studies have proposed black-box adversarial att…