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cs.CR2025
Defining Cost Function of Steganography with Large Language Models
Hanzhou Wu, Yige Wang
In this paper, we make the first attempt towards defining cost function of steganography with large language models (LLMs), which is totally different from previous works that rely…
cs.CR2025
Rotation, Scale, and Translation Resilient Black-box Fingerprinting for Intellectual Property Protection of EaaS Models
Hongjie Zhang, Zhiqi Zhao, Hanzhou Wu +2
Feature embedding has become a cornerstone technology for processing high-dimensional and complex data, which results in that Embedding as a Service (EaaS) models have been widely…
cs.CR2025
Yet Another Watermark for Large Language Models
Siyuan Bao, Ying Shi, Zhiguang Yang +2
Existing watermarking methods for large language models (LLMs) mainly embed watermark by adjusting the token sampling prediction or post-processing, lacking intrinsic coupling with…