ICLR 2018 Dataset
收藏arXiv2025-09-30 收录
下载链接：
https://github.com/n-boehmer/Combating-Collusion-Rings-is-Hard-but-Possible
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资源简介：
该数据集包含了2018年国际学习表征会议（ICLR '18）收到的所有论文及作者信息，用于计算评审员与论文之间的相似度评分。此外，该数据集还应用于分析评审周期，寻找最佳的评审分配方案。它支持计算多种类型的评审分配，包括最大权重和无循环的评审分配。该数据集的规模涉及911篇论文和2428位作者，其任务是为加权无循环评审提供支持。
This dataset encompasses all submitted papers and their associated author information for the International Conference on Learning Representations 2018 (ICLR '18). It is primarily utilized to compute the similarity scores between reviewers and papers, as well as to analyze the review cycle and identify the optimal review assignment strategy. The dataset supports the calculation of multiple types of review assignments, including maximum weight and acyclic review assignments. Comprising 911 papers and 2,428 authors, this dataset is dedicated to providing support for weighted acyclic review assignments.
提供机构：
ICLR
