67 citations · 142 across the 35 of their papers we have counts for
37 papers
What Survives Self-Evolution: Provenance Marks in Copied Agent Harnesses
Jieyu Li, Jingya Li, Sheng Li +2
Agent harnesses, the prompt and tool code around a base model, leak. Claude Code's 512,000 lines were mirrored within hours of a packaging error. A plagiarist can pass a leaked har…
ReVR: Dual-Path Concept Reasoning for Multimodal Fake News Detection
Zhikai Tan, Yuzhou Yang, Qichao Ying +4
Vision-language models (VLMs) support multimodal fake news detection (FND) by producing explicit analyses. Recent methods further improve interpretability by organizing verificatio…
Grounding and Explaining Visual Evidence for AI-Generated Image Detection in Human-Centric Scenes
Kun Guo, Yuzhou Yang, Haoyue Wang +3
Rapid advances in image generation models call for interpretable AI-generated image detection methods that not only determine authenticity but also provide supporting visual eviden…
RoE-FND: Synergizing LLMs with Experiential Learning for Effective and Generalizable Evidence-Based Fake News Detection
Yuzhou Yang, Qichao Ying, Sheng Li +3
The proliferation of deceptive content in social networks necessitates robust Fake News Detection (FND) systems. Existing pipelines either train detectors on labeled data or levera…
SimuFreeMark: A Noise-Simulation-Free Robust Watermarking Against Image Editing
Yichao Tang, Mingyang Li, Di Miao +3
The advancement of artificial intelligence generated content (AIGC) has created a pressing need for robust image watermarking that can withstand both conventional signal processing…
SyncGuard: Robust Audio Watermarking Capable of Countering Desynchronization Attacks
Zhenliang Gan, Xiaoxiao Hu, Sheng Li +2
Audio watermarking has been widely applied in copyright protection and source tracing. However, due to the inherent characteristics of audio signals, watermark localization and res…
MoFRR: Mixture of Diffusion Models for Face Retouching Restoration
Jiaxin Liu, Qichao Ying, Zhenxing Qian +4
The widespread use of face retouching on social media platforms raises concerns about the authenticity of face images. While existing methods focus on detecting face retouching, ho…
RoE-FND: A Case-Based Reasoning Approach with Dual Verification for Fake News Detection via LLMs
Yuzhou Yang, Yangming Zhou, Zhiying Zhu +3
The proliferation of deceptive content online necessitates robust Fake News Detection (FND) systems. While evidence-based approaches leverage external knowledge to verify claims, e…
CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models
Zhenzhen Ren, GuoBiao Li, Sheng Li +2
Despite providing superior performance, open-source large language models (LLMs) are vulnerable to abusive usage. To address this issue, recent works propose LLM fingerprinting met…
Adversarial Shallow Watermarking
Guobiao Li, Lei Tan, Yuliang Xue +4
Recent advances in digital watermarking make use of deep neural networks for message embedding and extraction. They typically follow the ``encoder-noise layer-decoder''-based archi…
Exploring Depth Information for Detecting Manipulated Face Videos
Haoyue Wang, Sheng Li, Ji He +3
Face manipulation detection has been receiving a lot of attention for the reliability and security of the face images/videos. Recent studies focus on using auxiliary information or…
Are handcrafted filters helpful for attributing AI-generated images?
Jialiang Li, Haoyue Wang, Sheng Li +3
Recently, a vast number of image generation models have been proposed, which raises concerns regarding the misuse of these artificial intelligence (AI) techniques for generating fa…
Cover-separable Fixed Neural Network Steganography via Deep Generative Models
Guobiao Li, Sheng Li, Zhenxing Qian +1
Image steganography is the process of hiding secret data in a cover image by subtle perturbation. Recent studies show that it is feasible to use a fixed neural network for data emb…
Purified and Unified Steganographic Network
Guobiao Li, Sheng Li, Zicong Luo +2
Steganography is the art of hiding secret data into the cover media for covert communication. In recent years, more and more deep neural network (DNN)-based steganographic schemes…
Object-oriented backdoor attack against image captioning
Meiling Li, Nan Zhong, Xinpeng Zhang +2
Backdoor attack against image classification task has been widely studied and proven to be successful, while there exist little research on the backdoor attack against vision-langu…
PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning
Xuntao Liu, Yuzhou Yang, Qichao Ying +3
Deceptive images can be shared in seconds with social networking services, posing substantial risks. Tampering traces, such as boundary artifacts and high-frequency information, ha…
From Covert Hiding to Visual Editing: Robust Generative Video Steganography
Xueying Mao, Xiaoxiao Hu, Wanli Peng +5
Traditional video steganography methods are based on modifying the covert space for embedding, whereas we propose an innovative approach that embeds secret message within semantic…
Steal My Artworks for Fine-tuning? A Watermarking Framework for Detecting Art Theft Mimicry in Text-to-Image Models
Ge Luo, Junqiang Huang, Manman Zhang +3
The advancement in text-to-image models has led to astonishing artistic performances. However, several studios and websites illegally fine-tune these models using artists' artworks…
PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection
Nan Zhong, Yiran Xu, Sheng Li +2
Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from rea…
Securing Fixed Neural Network Steganography
Zicong Luo, Sheng Li, Guobiao Li +2
Image steganography is the art of concealing secret information in images in a way that is imperceptible to unauthorized parties. Recent advances show that is possible to use a fix…
DRAW: Defending Camera-shooted RAW against Image Manipulation
Xiaoxiao Hu, Qichao Ying, Zhenxing Qian +2
RAW files are the initial measurement of scene radiance widely used in most cameras, and the ubiquitously-used RGB images are converted from RAW data through Image Signal Processin…
RetouchingFFHQ: A Large-scale Dataset for Fine-grained Face Retouching Detection
Qichao Ying, Jiaxin Liu, Sheng Li +3
The widespread use of face retouching filters on short-video platforms has raised concerns about the authenticity of digital appearances and the impact of deceptive advertising. To…
Towards Deep Network Steganography: From Networks to Networks
Guobiao Li, Sheng Li, Meiling Li +2
With the widespread applications of the deep neural network (DNN), how to covertly transmit the DNN models in public channels brings us the attention, especially for those trained…
Generative Steganographic Flow
Ping Wei, Ge Luo, Qi Song +3
Generative steganography (GS) is a new data hiding manner, featuring direct generation of stego media from secret data. Existing GS methods are generally criticized for their poor…