SciMRC：多视角科学机器阅读理解
SciMRC: Multi-perspective Scientific Machine Reading Comprehension
AI总结：
针对现有科学机器阅读理解数据集仅含单一视角的局限，本文提出包含初学者、学生和专家视角的多视角数据集SciMRC，实验证明其有效且具挑战性。
摘要：
科学机器阅读理解（SMRC）旨在通过给定问题与人交互来理解科学文本。据我们所知，目前仅有一个数据集专注于探索全文科学机器阅读理解。然而，该数据集忽略了不同读者可能对文本有不同理解程度的客观事实，仅包含单一视角的问答对，导致缺乏对不同视角的考量。为解决上述问题，我们提出了一种新颖的多视角SMRC数据集，名为SciMRC，其中包含了初学者、学生和专家的视角。我们提出的SciMRC由741篇科学论文和6,057个问答对构建而成。初学者、学生和专家的每个视角分别包含3,306、1,800和951个问答对。利用预训练模型在SciMRC上进行的广泛实验表明了考虑SMRC视角的重要性，并证明了该数据集对机器阅读理解具有挑战性。
英文摘要：
Scientific machine reading comprehension (SMRC) aims to understand scientific texts through interactions with humans by given questions. As far as we know, there is only one dataset focused on exploring full-text scientific machine reading comprehension. However, the dataset has ignored the fact that different readers may have different levels of understanding of the text, and only includes single-perspective question-answer pairs, leading to a lack of consideration of different perspectives. To tackle the above problem, we propose a novel multi-perspective SMRC dataset, called SciMRC, which includes perspectives from beginners, students and experts. Our proposed SciMRC is constructed from 741 scientific papers and 6,057 question-answer pairs. Each perspective of beginners, students and experts contains 3,306, 1,800 and 951 QA pairs, respectively. The extensive experiments on SciMRC by utilizing pre-trained models suggest the importance of considering perspectives of SMRC, and demonstrate its challenging nature for machine comprehension.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
