论文标题
Roft：一种评估人类检测机器生成文本的工具
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
论文作者
论文摘要
近年来，自然语言产生的大型神经网络（NLG）在产生流利文本的能力方面取得了飞跃。但是，评估NLG系统之间质量差异的任务以及了解人类对生成的文本的看法仍然至关重要和困难。在此系统演示中，我们提出了真实或假文本（ROFT），该网站通过邀请用户尝试在各种域中检测机器生成的文本来应对这两个挑战。我们介绍了一项新颖的评估任务，以检测到人工编写的过渡到机器生成的文本段落的边界。我们显示了使用ROFT评估机器生成新闻文章的检测的初步结果。
In recent years, large neural networks for natural language generation (NLG) have made leaps and bounds in their ability to generate fluent text. However, the tasks of evaluating quality differences between NLG systems and understanding how humans perceive the generated text remain both crucial and difficult. In this system demonstration, we present Real or Fake Text (RoFT), a website that tackles both of these challenges by inviting users to try their hand at detecting machine-generated text in a variety of domains. We introduce a novel evaluation task based on detecting the boundary at which a text passage that starts off human-written transitions to being machine-generated. We show preliminary results of using RoFT to evaluate detection of machine-generated news articles.
