1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
RMCW: A Deletion-Robust Watermark Based on Reed--Muller Codes for Language Models
Yi Wang, Baicheng Chen, Yu Wang +3
Large Language Model (LLM) watermarking provides a lightweight mechanism for identifying text generated by a specific model, but its robustness remains fragile under post-processin…
CREBench: Evaluating Large Language Models in Cryptographic Binary Reverse Engineering
Baicheng Chen, Yu Wang, Ziheng Zhou +4
Reverse engineering (RE) is central to software security, particularly for cryptographic programs that handle sensitive data and are highly prone to vulnerabilities. It supports cr…
Reverse-Engineering Model Editing on Language Models
Zhiyu Sun, Minrui Luo, Yu Wang +2
Large language models (LLMs) are pretrained on corpora containing trillions of tokens and, therefore, inevitably memorize sensitive information. Locate-then-edit methods, as a main…
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
Yu Wang, Yijian Liu, Liheng Ji +11
We build \textbf{AICrypto}, a comprehensive benchmark designed to evaluate the cryptography capabilities of large language models (LLMs). The benchmark comprises 135 multiple-choic…
SATA: A Paradigm for LLM Jailbreak via Simple Assistive Task Linkage
Xiaoning Dong, Wenbo Hu, Wei Xu +1
Large language models (LLMs) have made significant advancements across various tasks, but their safety alignment remain a major concern. Exploring jailbreak prompts can expose LLMs…