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cs.CL2025

Dynamically Allocated Interval-Based Generative Linguistic Steganography with Roulette Wheel

Yihao Wang, Ruiqi Song, Lingxiao Li +2

Existing linguistic steganography schemes often overlook the conditional probability (CP) of tokens in the candidate pool, allocating the one coding to all tokens, which results in…

cs.CL2024

State-of-the-art Advances of Deep-learning Linguistic Steganalysis Research

Yihao Wang, Ru Zhang, Yifan Tang +1

With the evolution of generative linguistic steganography techniques, conventional steganalysis falls short in robustly quantifying the alterations induced by steganography, thereb…

cs.CL2024

Linguistic Steganalysis via LLMs: Two Modes for Efficient Detection of Strongly Concealed Stego

Yifan Tang, Yihao Wang, Ru Zhang +1

To detect stego (steganographic text) in complex scenarios, linguistic steganalysis (LS) with various motivations has been proposed and achieved excellent performance. However, wit…

cs.CL2024

An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration

Yihao Li, Ru Zhang, Jianyi Liu

While Large Language Models (LLMs) demonstrate exceptional performance in a multitude of Natural Language Processing (NLP) tasks, they encounter challenges in practical application…

cs.CL2024

UP4LS: User Profile Constructed by Multiple Attributes for Enhancing Linguistic Steganalysis

Yihao Wang, Ruiqi Song, Lingxiao Li +3

Linguistic steganalysis (LS) tasks aim to detect whether a text contains secret information. Existing LS methods focus on the deep-learning model design and they achieve excellent…