SciMRC: Multi-perspective Scientific Machine Reading Comprehension
Xiao Zhang Heqi Zheng Yuxiang Nie Heyan Huang Xian-Ling Mao
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.