TAILOR-CGO

该数据集名为TAILOR-CGO，包含了来自6个不同大型语言模型生成的22,400条独特的定制化回应。这些回应被标记为绝对分数或成对排名，旨在评估回应与提供的关于疫苗关注的共同观点（Common-Ground Opinions，简称CGOs）的契合程度。该数据集旨在评估针对基于VaxConcerns分类法的疫苗关注问题所生成的回应，这些回应是根据公众意见调查问题中产生的特定观点定制的。规模上，数据集包含了22,400条独特的回应，其任务是针对共同观点（CGOs）定制疫苗干预措施。

The dataset named TAILOR-CGO contains 22,400 unique customized responses generated by six distinct large language models. These responses are annotated with absolute scores or pairwise rankings, aiming to evaluate the alignment between the responses and the provided common-ground opinions (Common-Ground Opinions, abbreviated as CGOs) regarding vaccine concerns. This dataset is designed to evaluate responses generated for vaccine-related concern questions based on the VaxConcerns taxonomy, where the responses are customized based on specific opinions derived from public opinion survey questions. With 22,400 unique entries in total, its core task is to customize vaccine interventions tailored to common-ground opinions (CGOs).