21 citations · 35 across the 11 of their papers we have counts for
4 papers · 1 filter
Measuring Diversity in Synthetic Datasets
Yuchang Zhu, Huizhe Zhang, Bingzhe Wu +5
Large language models (LLMs) are widely adopted to generate synthetic datasets for various natural language processing (NLP) tasks, such as text classification and summarization. H…
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping
Haoyu Wang, Guozheng Ma, Ziqiao Meng +9
Self-alignment is an effective way to reduce the cost of human annotation while ensuring promising model capability. However, most current methods complete the data collection and…
WatME: Towards Lossless Watermarking Through Lexical Redundancy
Liang Chen, Yatao Bian, Yang Deng +4
Text watermarking has emerged as a pivotal technique for identifying machine-generated text. However, existing methods often rely on arbitrary vocabulary partitioning during decodi…
Are Large Language Models Really Robust to Word-Level Perturbations?
Haoyu Wang, Guozheng Ma, Cong Yu +10
The swift advancement in the scales and capabilities of Large Language Models (LLMs) positions them as promising tools for a variety of downstream tasks. In addition to the pursuit…