论文标题
对多跳机阅读理解方法的全面调查
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches
论文作者
论文摘要
机器阅读理解（MRC）是自然语言处理（NLP）的长期话题。 MRC任务旨在根据给定上下文回答问题。最近的研究集中于多跳的MRC，这是MRC的更具挑战性的扩展，该问题需要在整个上下文中回答一些脱节信息。由于多跳MRC的复杂性和重要性，近年来已经重点介绍了大量研究，因此，这是必要的，值得回顾相关文献。这项研究旨在根据2018年至2022年的31项研究来调查多跳跃MRC方法的最新进展。在这方面，首先将引入多跳的MRC问题定义，然后将对31个模型进行详细审查，并强烈关注其多跳跃方面。他们还将根据其主要技术进行分类。最后，将介绍对模型和技术的细粒综合比较。
Machine reading comprehension (MRC) is a long-standing topic in natural language processing (NLP). The MRC task aims to answer a question based on the given context. Recently studies focus on multi-hop MRC which is a more challenging extension of MRC, which to answer a question some disjoint pieces of information across the context are required. Due to the complexity and importance of multi-hop MRC, a large number of studies have been focused on this topic in recent years, therefore, it is necessary and worth reviewing the related literature. This study aims to investigate recent advances in the multi-hop MRC approaches based on 31 studies from 2018 to 2022. In this regard, first, the multi-hop MRC problem definition will be introduced, then 31 models will be reviewed in detail with a strong focus on their multi-hop aspects. They also will be categorized based on their main techniques. Finally, a fine-grain comprehensive comparison of the models and techniques will be presented.
