NormDial：用于建模社会规范遵守与违反的可比较双语合成对话数据集
NormDial: A Comparable Bilingual Synthetic Dialog Dataset for Modeling Social Norm Adherence and Violation
AI总结：
提出双语合成对话数据集NormDial，通过人机协同流程生成中美文化社会规范遵守与违反的逐轮标注，并评估现有大模型在规范检测任务上的表现。
摘要：
社会规范从根本上塑造了人际交流。我们提出了NormDial，一个高质量的双人对话数据集，包含针对中美文化的社会规范遵守与违反的逐轮标注。引入社会规范遵守检测任务，我们的数据集使用人机协同流程，通过用少量专家标注的社会规范提示大型语言模型，以中英双语合成生成。我们通过人工评估证明生成的对话质量很高，并进一步评估了现有大型语言模型在此任务上的表现。我们的发现为理解社会规范在跨语言和文化的对话语境中表现的细微差别指明了新方向。
英文摘要：
Social norms fundamentally shape interpersonal communication. We present NormDial, a high-quality dyadic dialogue dataset with turn-by-turn annotations of social norm adherences and violations for Chinese and American cultures. Introducing the task of social norm observance detection, our dataset is synthetically generated in both Chinese and English using a human-in-the-loop pipeline by prompting large language models with a small collection of expert-annotated social norms. We show that our generated dialogues are of high quality through human evaluation and further evaluate the performance of existing large language models on this task. Our findings point towards new directions for understanding the nuances of social norms as they manifest in conversational contexts that span across languages and cultures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
