collaborators

5 papers

cs.CR2026

Protecting Creative Writing Copyright against AI Imitation via Implicit Watermarking

Ziwei Zhang, Juan Wen, Wanli Peng +3

Large language models (LLMs) enable powerful knowledge injection through approaches such as in-context learning and fine-tuning, but they also introduce new risks of unauthorized i…

cs.CR2025

Self-Disguise Attack: Induce the LLM to disguise itself for AIGT detection evasion

Yinghan Zhou, Juan Wen, Wanli Peng +3

AI-generated text (AIGT) detection evasion aims to reduce the detection probability of AIGT, helping to identify weaknesses in detectors and enhance their effectiveness and reliabi…

cs.CL2025

Kill two birds with one stone: generalized and robust AI-generated text detection via dynamic perturbations

Yinghan Zhou, Juan Wen, Wanli Peng +3

The growing popularity of large language models has raised concerns regarding the potential to misuse AI-generated text (AIGT). It becomes increasingly critical to establish an exc…

cs.CR2025

GTSD: Generative Text Steganography Based on Diffusion Model

Zhengxian Wu, Juan Wen, Yiming Xue +2

With the rapid development of deep learning, existing generative text steganography methods based on autoregressive models have achieved success. However, these autoregressive steg…

cs.CL2025

BadApex: Backdoor Attack Based on Adaptive Optimization Mechanism of Black-box Large Language Models

Zhengxian Wu, Juan Wen, Wanli Peng +3

Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned a…