4 papers
Adaptive Testing for Segmenting Watermarked Texts From Language Models
Xingchi Li, Xiaochi Liu, Guanxun Li
The rapid adoption of large language models (LLMs), such as GPT-4 and Claude 3.5, underscores the need to distinguish LLM-generated text from human-written content to mitigate the…
A General Framework for Multiple Testing via E-value Aggregation and Data-Dependent Weighting
Guanxun Li, Xianyang Zhang
Motivated by recent findings in Li and Zhang (2025), which established an equivalence between certain p-value-based multiple testing procedures and the e-Benjamini-Hochberg procedu…
Segmenting Watermarked Texts From Language Models
Xingchi Li, Guanxun Li, Xianyang Zhang
Watermarking is a technique that involves embedding nearly unnoticeable statistical signals within generated content to help trace its source. This work focuses on a scenario where…
Importance is Important: Generalized Markov Chain Importance Sampling Methods
Guanxun Li, Aaron Smith, Quan Zhou
We show that for any multiple-try Metropolis algorithm, one can always accept the proposal and evaluate the importance weight that is needed to correct for the bias without extra c…