4 papers
ToReMi: Topic-Aware Data Reweighting for Dynamic Pre-Training Data Selection
Xiaoxuan Zhu, Zhouhong Gu, Baiqian Wu +5
Pre-training large language models (LLMs) necessitates enormous diverse textual corpora, making effective data selection a key challenge for balancing computational resources and m…
LITE: LLM-Impelled efficient Taxonomy Evaluation
Lin Zhang, Zhouhong Gu, Suhang Zheng +4
This paper presents LITE, an LLM-based evaluation method designed for efficient and flexible assessment of taxonomy quality. To address challenges in large-scale taxonomy evaluatio…
GAPO: Learning Preferential Prompt through Generative Adversarial Policy Optimization
Zhouhong Gu, Xingzhou Chen, Xiaoran Shi +5
Recent advances in large language models have highlighted the critical need for precise control over model outputs through predefined constraints. While existing methods attempt to…
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection
Yifeng Wang, Zhouhong Gu, Siwei Zhang +5
Explainable fake news detection predicts the authenticity of news items with annotated explanations. Today, Large Language Models (LLMs) are known for their powerful natural langua…