33 citations · 50 across the 8 of their papers we have counts for
8 papers
Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection
Xiao Pu, Zepeng Cheng, Lin Yuan +2
As large language models (LLMs) generate text that increasingly resembles human writing, the subtle cues that distinguish AI-generated content from human-written content become inc…
: A Black-Box Scrubbing Attack on LLM Watermarks
Baizhou Huang, Xiao Pu, Xiaojun Wan
Watermarking has emerged as a prominent technique for LLM-generated content detection by embedding imperceptible patterns. Despite supreme performance, its robustness against adver…
Style-Compress: An LLM-Based Prompt Compression Framework Considering Task-Specific Styles
Xiao Pu, Tianxing He, Xiaojun Wan
Prompt compression condenses contexts while maintaining their informativeness for different usage scenarios. It not only shortens the inference time and reduces computational costs…
Better than Random: Reliable NLG Human Evaluation with Constrained Active Sampling
Jie Ruan, Xiao Pu, Mingqi Gao +2
Human evaluation is viewed as a reliable evaluation method for NLG which is expensive and time-consuming. To save labor and costs, researchers usually perform human evaluation on a…
LLM-based NLG Evaluation: Current Status and Challenges
Mingqi Gao, Xinyu Hu, Jie Ruan +2
Evaluating natural language generation (NLG) is a vital but challenging problem in natural language processing. Traditional evaluation metrics mainly capturing content (e.g. n-gram…
On the Zero-Shot Generalization of Machine-Generated Text Detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han +2
The rampant proliferation of large language models, fluent enough to generate text indistinguishable from human-written language, gives unprecedented importance to the detection of…
Summarization is (Almost) Dead
Xiao Pu, Mingqi Gao, Xiaojun Wan
How well can large language models (LLMs) generate summaries? We develop new datasets and conduct human evaluation experiments to evaluate the zero-shot generation capability of LL…
Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks
Xiao Pu, Mingqi Gao, Xiaojun Wan
Research on automated text summarization relies heavily on human and automatic evaluation. While recent work on human evaluation mainly adopted intrinsic evaluation methods, judgin…