8 papers
DNA: Dual-stage Native Attribution for Generated Image Source Tracing
Chao Wang, Kejiang Chen, Zijin Yang +4
The paper proposes DNA, a two‑stage framework that attributes generated images to their source models without additional training by first screening at the family level and then pi…
ReTokSync: Self-Synchronizing Tokenization Disambiguation for Generative Linguistic Steganography
Yaofei Wang, Rui Wang, Weilong Pang +4
Generative linguistic steganography (GLS) enables covert communication by embedding secret messages into the natural language generation process. In practical deployment, however,…
SWIFT: Sliding Window Reconstruction for Few-Shot Training-Free Generated Video Attribution
Chao Wang, Zijin Yang, Yaofei Wang +4
Recent advancements in video generation technologies have been significant, resulting in their widespread application across multiple domains. However, concerns have been mounting…
InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model
Meng Tong, Kejiang Chen, Jie Zhang +5
Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unau…
STEAD: Robust Provably Secure Linguistic Steganography with Diffusion Language Model
Yuang Qi, Na Zhao, Qiyi Yao +4
Recent provably secure linguistic steganography (PSLS) methods rely on mainstream autoregressive language models (ARMs) to address historically challenging tasks, that is, to disgu…
PSRT: Accelerating LRM-based Guard Models via Prefilled Safe Reasoning Traces
Jiawei Zhao, Yuang Qi, Weiming Zhang +2
Large Reasoning Models (LRMs) have demonstrated remarkable performance on tasks such as mathematics and code generation. Motivated by these strengths, recent work has empirically d…