ACL-OCL

该数据集名为ACL-OCL，经过丰富更新，包含了引文计数、参考文献的标题和摘要，以及标注的研究假设。作为目前最大的OpenReview提交数据集，它为预测引文计数和评审得分提供了深入见解。此外，该数据集还包含了诸如引文计数和研究假设等元数据，并且可以通过Huggingface的脚本完全访问。在规模上，它是最大的OpenReview提交数据集，其任务包括引文计数预测和评审得分预测。This dataset, named ACL-OCL, has been extensively updated and includes citation counts, titles and abstracts of cited references, as well as annotated research hypotheses. As the largest OpenReview submission dataset currently available, it provides in-depth insights for predicting citation counts and review scores. In addition, the dataset contains metadata such as citation counts and research hypotheses, and is fully accessible via Hugging Face scripts. In terms of scale, it remains the largest OpenReview submission dataset, with its supported tasks covering citation count prediction and review score prediction.

搜集汇总

背景与挑战

背景概述

ACL-OCL是学术文档质量预测（SDQP）数据集的一个子集，专门用于引用计数预测任务，基于ACL-OCL数据集扩展并包含更新后的引用数据和注释假设。该数据集包含约6万行学术论文数据，涵盖标题、摘要、引用计数、评审分数等丰富字段，适用于机器学习模型训练和评估。