1 citations · 2 across the 3 of their papers we have counts for
4 papers
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…
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…
RAFT: Realistic Attacks to Fool Text Detectors
James Wang, Ran Li, Junfeng Yang +1
Large language models (LLMs) have exhibited remarkable fluency across various tasks. However, their unethical applications, such as disseminating disinformation, have become a grow…
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…