6 papers
Early Detection of Misinformation for Infodemic Management: A Domain Adaptation Approach
Minjia Mao, Xiaohang Zhao, Xiao Fang
An infodemic refers to an enormous amount of true information and misinformation disseminated during a disease outbreak. Detecting misinformation at the early stage of an infodemic…
Early Stopping Chain-of-thoughts in Large Language Models
Minjia Mao, Bowen Yin, Yu Zhu +1
Reasoning large language models (LLMs) have demonstrated superior capacities in solving complicated problems by generating long chain-of-thoughts (CoT), but such a lengthy CoT incu…
Measuring Stereotype and Deviation Biases in Large Language Models
Daniel Wang, Eli Brignac, Minjia Mao +1
Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study, we investigate two types of bia…
A General Method for Detecting Information Generated by Large Language Models
Minjia Mao, Dongjun Wei, Xiao Fang +1
The proliferation of large language models (LLMs) has significantly transformed the digital information landscape, making it increasingly challenging to distinguish between human-w…
Short-PHD: Detecting Short LLM-generated Text with Topological Data Analysis After Off-topic Content Insertion
Dongjun Wei, Minjia Mao, Xiao Fang +1
The malicious usage of large language models (LLMs) has motivated the detection of LLM-generated texts. Previous work in topological data analysis shows that the persistent homolog…
Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method
Minjia Mao, Dongjun Wei, Zeyu Chen +2
Recent advancements in large language models (LLMs) have highlighted the risk of misusing them, raising the need for accurate detection of LLM-generated content. In response, a via…