论文标题
解释链：生成更高质量自然语言解释的新提示方法
Chain of Explanation: New Prompting Method to Generate Higher Quality Natural Language Explanation for Implicit Hate Speech
论文作者
论文摘要
最近的研究利用了先进的生成语言模型来生成自然语言解释（NLE），以说明某个文本可能会令人讨厌。我们提出了使用启发式词语和目标群体的解释链（COE）提示方法，以生成高质量的nle，以实现隐式仇恨言论。通过提供准确的目标信息，我们将蓝色得分从44.0提高到62.3。然后，我们使用各种自动指标以及信息性和清晰度分数的人类注释来评估生成的NLE的质量。
Recent studies have exploited advanced generative language models to generate Natural Language Explanations (NLE) for why a certain text could be hateful. We propose the Chain of Explanation (CoE) Prompting method, using the heuristic words and target group, to generate high-quality NLE for implicit hate speech. We improved the BLUE score from 44.0 to 62.3 for NLE generation by providing accurate target information. We then evaluate the quality of generated NLE using various automatic metrics and human annotations of informativeness and clarity scores.
