论文标题
多跳机阅读理解数据集和指标的全面调查
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metrics
论文作者
论文摘要
多跳机阅读理解是一项具有挑战性的任务，目的是根据不同段落的信息回答问题。评估指标和数据集是多跳跃MRC的重要组成部分，因为没有它们的情况下不可能训练和评估模型，而且数据集的拟议挑战通常是改善现有模型的重要动机。由于对该领域的关注越来越大，因此有必要详细介绍它们。这项研究旨在介绍多跳MRC评估指标和数据集的最新进展的全面调查。在这方面，首先将介绍多跳的MRC问题定义，然后将研究基于其多跳的评估指标。此外，从2017年到2022年，对15个多跳数据集进行了详细审查，最后已经准备了全面的分析。最后，已经讨论了该领域的公开问题。
Multi-hop Machine reading comprehension is a challenging task with aim of answering a question based on disjoint pieces of information across the different passages. The evaluation metrics and datasets are a vital part of multi-hop MRC because it is not possible to train and evaluate models without them, also, the proposed challenges by datasets often are an important motivation for improving the existing models. Due to increasing attention to this field, it is necessary and worth reviewing them in detail. This study aims to present a comprehensive survey on recent advances in multi-hop MRC evaluation metrics and datasets. In this regard, first, the multi-hop MRC problem definition will be presented, then the evaluation metrics based on their multi-hop aspect will be investigated. Also, 15 multi-hop datasets have been reviewed in detail from 2017 to 2022, and a comprehensive analysis has been prepared at the end. Finally, open issues in this field have been discussed.
