3 papers
cs.LG2025
Transformers in Pseudo-Random Number Generation: A Dual Perspective on Theory and Practice
Ran Li, Lingshu Zeng
Pseudo-random number generators (PRNGs) are high-nonlinear processes, and they are key blocks in optimization of Large language models. Transformers excel at processing complex non…
cs.LG2025
LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs
Ran Li, Hao Wang, Chengzhi Mao
Efficient red-teaming method to uncover vulnerabilities in Large Language Models (LLMs) is crucial. While recent attacks often use LLMs as optimizers, the discrete language space m…
cs.CL2025
Learning to Rewrite: Generalized LLM-Generated Text Detection
Ran Li, Wei Hao, Weiliang Zhao +2
Large language models (LLMs) present significant risks when used to generate non-factual content and spread disinformation at scale. Detecting such LLM-generated content is crucial…