以下是一篇由清华大学的研究者们发布在arXiv上的中文文章示例：

标题：ERNIE 2.0: A Continual Pre-training Framework for Language Understanding

摘要：本文提出了一个基于Transformer架构的预训练模型ERNIE 2.0，该模型通过多任务学习、知识蒸馏和领域自适应等技术实现了持续预训练。实验结果表明，ERNIE 2.0在各类中文自然语言处理任务上表现优异，并且具有较好的可迁移性和通用性。

正文：由于篇幅限制，在此无法给出完整的正文内容，请您见谅。
基于以上这段文本，重新叙述一遍。
The article on arXiv by researchers from Tsinghua University introduces a pre-training model called ERNIE 2.0, based on the Transformer architecture. The model uses techniques such as multi-task learning, knowledge distillation, and domain adaptation to achieve continual pre-training. Experimental results demonstrate that ERNIE 2.0 performs well on various Chinese natural language processing tasks, with good transferability and versatility. Unfortunately, due to space limitations, the entire body of the article cannot be provided.