7 papers
TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency
Jiuan Zhou, Yuhao Xue, Yu Cheng +2
Generative text steganography enables LLM agents to exchange secret information through task-relevant messages. Yet most methods evaluate recovery on sender-side tokens, whereas th…
FGAS: Fixed Decoder Network-Based Audio Steganography with Adversarial Perturbation Generation
Jialin Yan, Yu Cheng, Zhaoxia Yin +4
The rapid development of Artificial Intelligence Generated Content (AIGC) has made high-fidelity generated audio widely available across the Internet, driving the advancement of au…
Face-D(^2)CL: Multi-Domain Synergistic Representation with Dual Continual Learning for Facial DeepFake Detection
Yushuo Zhang, Yu Cheng, Yongkang Hu +4
Facial forgery techniques are advancing rapidly, posing severe threats to public trust and information security while imposing higher demands on the continual adaptation of DeepFak…
DTAMS: High-Capacity Generative Steganography via Dynamic Multi-Timestep Selection and Adaptive Deviation Mapping in Latent Diffusion
Yuhao Xue, Jiuan Zhou, Yu Cheng +1
With the rapid development of AIGC technologies, generative image steganography has attracted increasing attention due to its high imperceptibility and flexibility. However, existi…
SAIDO: Generalizable Detection of AI-Generated Images via Scene-Aware and Importance-Guided Dynamic Optimization in Continual Learning
Yongkang Hu, Yu Cheng, Yushuo Zhang +2
The widespread misuse of image generation technologies has raised security concerns, driving the development of AI-generated image detection methods. However, generalization has be…
DynaQuant: Dynamic Mixed-Precision Quantization for Learned Image Compression
Youneng Bao, Yulong Cheng, Yiping Liu +4
Prevailing quantization techniques in Learned Image Compression (LIC) typically employ a static, uniform bit-width across all layers, failing to adapt to the highly diverse data di…